Genetic algorithms in chemometrics
This review covers the application of Genetic Algorithms (GAs) in Chemometrics. The first applications of GAs in chemistry date back to the 1970s, and in the last decades, they have been more and more frequently used to solve different kinds of problems, for example, when the objective functions do...
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| Published in | Journal of chemometrics Vol. 26; no. 6; pp. 345 - 351 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Chichester, UK
John Wiley & Sons, Ltd
01.06.2012
Wiley Subscription Services, Inc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0886-9383 1099-128X |
| DOI | 10.1002/cem.2426 |
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| Abstract | This review covers the application of Genetic Algorithms (GAs) in Chemometrics. The first applications of GAs in chemistry date back to the 1970s, and in the last decades, they have been more and more frequently used to solve different kinds of problems, for example, when the objective functions do not possess properties such as continuity, differentiability, and so on. These algorithms maintain and manipulate a family, or population, of solutions and implement a “survival of the fittest” strategy in their search for better solutions. GAs are very useful in the optimization and variable selection in modeling and calibration because of the strong effect of the relationship between presence/absence of variables in a calibration model and the prediction ability of the model itself. This review is not a complete summary of the applications of GAs to chemometric problems; its goal is rather to show the researchers the main fields of application of GAs, together with providing a list of references on the subject. Copyright © 2012 John Wiley & Sons, Ltd.
The first applications of Genetic Algorithms (GAs) in chemistry date back to the 1970s, and in the last decades, they have been more and more frequently used to solve different kinds of problems, for example, when the objective functions do not possess properties such as continuity, differentiability, and so on. GAs are very useful in the optimization and variable selection in modeling and calibration because of the strong effect of the relationship between presence/absence of variables in a calibration model and the prediction ability of the model itself. |
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| AbstractList | This review covers the application of Genetic Algorithms (GAs) in Chemometrics. The first applications of GAs in chemistry date back to the 1970s, and in the last decades, they have been more and more frequently used to solve different kinds of problems, for example, when the objective functions do not possess properties such as continuity, differentiability, and so on. These algorithms maintain and manipulate a family, or population, of solutions and implement a “survival of the fittest” strategy in their search for better solutions. GAs are very useful in the optimization and variable selection in modeling and calibration because of the strong effect of the relationship between presence/absence of variables in a calibration model and the prediction ability of the model itself. This review is not a complete summary of the applications of GAs to chemometric problems; its goal is rather to show the researchers the main fields of application of GAs, together with providing a list of references on the subject. Copyright © 2012 John Wiley & Sons, Ltd.
The first applications of Genetic Algorithms (GAs) in chemistry date back to the 1970s, and in the last decades, they have been more and more frequently used to solve different kinds of problems, for example, when the objective functions do not possess properties such as continuity, differentiability, and so on. GAs are very useful in the optimization and variable selection in modeling and calibration because of the strong effect of the relationship between presence/absence of variables in a calibration model and the prediction ability of the model itself. This review covers the application of Genetic Algorithms (GAs) in Chemometrics. The first applications of GAs in chemistry date back to the 1970s, and in the last decades, they have been more and more frequently used to solve different kinds of problems, for example, when the objective functions do not possess properties such as continuity, differentiability, and so on. These algorithms maintain and manipulate a family, or population, of solutions and implement a "survival of the fittest" strategy in their search for better solutions. GAs are very useful in the optimization and variable selection in modeling and calibration because of the strong effect of the relationship between presence/absence of variables in a calibration model and the prediction ability of the model itself. This review is not a complete summary of the applications of GAs to chemometric problems; its goal is rather to show the researchers the main fields of application of GAs, together with providing a list of references on the subject. [PUBLICATION ABSTRACT] |
| Author | Niazi, Ali Leardi, Riccardo |
| Author_xml | – sequence: 1 givenname: Ali surname: Niazi fullname: Niazi, Ali organization: Department of Chemistry, Islamic Azad University, Arak Branch, Arak, Iran – sequence: 2 givenname: Riccardo surname: Leardi fullname: Leardi, Riccardo email: riclea@dictfa.unige.it, R. Leardi, Department of Pharmaceutical and Food Chemistry and Technology, Genova University, Via Brigata Salerno (Ponte), I-16147 Genova, Italy., riclea@dictfa.unige.it organization: Department of Pharmaceutical and Food Chemistry and Technology, Genova University, Via Brigata Salerno (Ponte), I-16147, Genova, Italy |
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| Cites_doi | 10.1016/j.chemolab.2004.07.004 10.1016/j.ejmech.2006.12.020 10.1021/jp026114 10.1016/S0922-3487(03)23010-0 10.1016/S0169-7439(02)00068-0 10.1016/S0166-1280(02)00619-X 10.1002/adic.200690087 10.1016/j.chemolab.2003.11.006 10.1002/cem.651 10.1016/j.memsci.2010.09.026 10.1016/S0169-7439(98)00135-X 10.1016/S0009-2614(02)01547-6 10.1021/ci060087t 10.1021/ci0255228 10.1016/S0003-2670(00)01114-4 10.1016/B978-012213810-2/50003-7 10.1016/S0922-3487(03)23001-X 10.1021/ac980451q 10.1016/j.chemolab.2006.04.004 10.1016/j.talanta.2010.07.062 10.1016/S0003-2670(01)00910-2 10.1002/cem.1000 10.2116/analsci.20.1701 10.1021/ac00119a015 10.1002/app.29609 10.1016/j.chroma.2007.04.025 10.1016/0169-7439(93)80028-G 10.1016/0165-9936(91)85132-B 10.1021/ci049763m 10.1016/0003-2670(95)00163-T 10.1002/(SICI)1099-128X(199605)10:3<253::AID-CEM420>3.0.CO;2-Z 10.1002/(SICI)1096-987X(19970715)18:9<1233::AID-JCC11>3.0.CO;2-6 10.1016/S0003-2670(02)00272-6 10.1016/j.aca.2006.12.023 10.1016/S0169-7439(02)00033-3 10.1016/S0169-7439(98)00051-3 10.1016/S0922-3487(03)23002-1 10.1016/S0165-9936(97)00085-X 10.1016/j.seppur.2010.09.017 10.1081/SL-100001446 10.1038/376209a0 10.1002/cem.1180060506 10.1016/j.aca.2011.02.004 10.1080/10408340600969924 10.1016/S0169-7439(03)00091-1 10.1556/JPC.18.2005.2.5 10.1016/j.desal.2011.01.083 10.1016/j.aca.2004.03.048 10.1021/ac00073a006 10.1365/s10337-008-0608-4 10.1016/S0003-2670(97)00065-2 10.1255/jnirs.394 10.1366/000370210791666246 10.1016/0169-7439(93)80031-C 10.1016/S0013-4686(97)00139-4 10.1016/j.saa.2008.03.005 10.1016/S0003-2670(97)00033-0 10.1002/cem.812 10.1016/j.jmgm.2008.03.004 10.1016/j.aca.2006.01.048 10.1021/jm990472s 10.1016/S0003-2670(99)00081-1 10.2116/analsci.26.897 10.1016/S0165-2370(99)00002-9 10.1021/ci025661p 10.1007/BF00124503 10.1016/j.chemolab.2009.03.003 10.1016/0169-7439(93)80079-W 10.1016/S0169-7439(98)00148-8 10.1126/science.8346439 10.1002/1099-128X(200009/12)14:5/6<643::AID-CEM621>3.0.CO;2-E 10.1016/S0922-3487(03)23012-4 10.1021/ci9901284 10.1016/0301-4622(94)00130-C 10.1149/1.3517476 10.1007/s10910-011-9832-5 10.1366/0003702001951237 10.1007/s00604-005-0334-7 10.1016/S0922-3487(03)23006-9 10.1021/ci990010n 10.1021/j100141a013 10.1002/app.33252 10.1016/S0169-7439(96)00028-7 10.1016/j.commatsci.2008.04.032 10.1016/S0003-2670(03)00468-9 10.1002/(SICI)1096-987X(199903)20:4<455::AID-JCC6>3.0.CO;2-1 10.1255/jnirs.192 10.1016/j.aca.2004.05.067 10.1080/00032710600755868 10.1002/anie.199522801 10.1016/S0169-7439(02)00104-1 10.1016/S0921-4526(98)00398-6 10.1002/qsar.200630159 10.1002/elan.200403204 10.1002/cem.1339 10.1016/S0922-3487(03)23004-5 10.1002/cem.891 10.1016/j.chemolab.2010.02.003 10.1016/0003-2670(94)80155-X 10.1021/ac9715884 10.1016/S0169-7439(96)00062-7 10.1016/S0165-9936(98)00011-9 10.1016/S0169-7439(01)00156-3 10.1016/0009-2614(96)01009-3 10.1016/S0169-7439(98)00085-9 10.1016/S0039-9140(02)00505-2 10.1007/BF00202038 10.1134/S1061934807040090 |
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| References | Maiocchi A. Genetic algorithms in molecular modeling: a review. Data Handl. Sci. Techn. 2003; 23: 109-139. Hervas C. Algar JA, Silva M. Correction of temperature variations in kinetic-based determinations by use of pruning computational neural networks in conjucation with gentic algorithms. J. Chem. Inf. Comp. Sci. 2000; 40: 724-731. Niazi A, Jameh-Bozorghi S, Nori-Shargh D. Prediction of acidity constants of thiazolidine-4-carbozylic acid derivatives using Ab initio and genetic algorithm-partial least squares. Turk. J. Chem. 2006; 30: 619-628. Shaffer RE, Small GW. Learning optimization from nature: simulated annealing and genetic algorithms. Anal. Chem. 1997; 69: 236A-242A. Hou TJ, Wang JM, Li YY, Xu XY. Application of genetic algorithm to the QSAR research of pyrrolobenzothiazepinones and pyrrolobenzoxazepinone-novel and specific non-nucleoside HIV-1 reverse transcription inhibitors. Chin. Chem. Lett. 1998; 9: 651-654. Acros MJ, Alonso C, Ortiz MC. Genetic-algorithm-based potential selection in multivariate voltammetric determination of idomethacin and acemethacin by partial least squares. Electrochim. Acta 1998; 43: 479-485. Hibbert DB. Hybrid genetic algorithms. Data Handl. Sci. Techn. 2003; 23: 55-68. Holland JH. Adaptation in Natural and Artificial Systems. The University of Michigan Press, Michigan, 1975. Wang J, Krudy G, Xie XQ, Wu C, Holland G. Genetic algorithm-optimized QSPR model for bioavailability, protein binding, and urinary excretion. J. Chem. Inf. Model. 2006; 46: 2674-2683. Ghasemi J, Niazi A, Leardi R. Genetic-algorithm-based wavelength selection in multicomponent spectrophotometric determination by PLS: application on copper and zinc mixture. Talanta 2003; 59: 311-317. Leardi R, Boggia R, Terrile M. Genetic algorithms as a strategy for feature selection. J. Chemometr. 1992; 6: 267-281. Lucasius CB, Kateman G. Understanding and using genetic algorithms. Part 1: concepts, properties and context. Chemometr. Intell. Lab 1993; 19: 1-33. Hou TJ, Wang JM, Xu XJ. Applications of genetic algorithms on the structure-activity correlation study of a group of nin-nucleoside HIV-1 inhibitors. Chemometr. Intell. Lab 1999; 45: 303-310. Wehrens R, Buydens LMC. Evolutionary optimization: a tutorial. Trends Anal. Chem. 1997; 17: 193-203. Maddox J. Genetics helping molecular dynamics. Nature 1995; 376: 209. Brodhurst D, Goodacre R, Jones A, Rowland JJ, Kell DB. Genetic algorithms as a method for variable selection in multiple linear regression and partial least squares regression. Anal. Chim. Acta 1997; 348: 71-86. Broudiscou A, Leardi R, Phan-Tan-Luu R. Genetic algorithm as a tool for selection of D-optimal design. Chemometr. Intell. Lab 1996; 35: 105-116. Leardi R. Genetic algorithms in chemometrics and chemistry: a review. J. Chemometr. 2001; 15: 559-569. Babic S, Horvat AJM, Kastelan-Macan M. Use of a genetic algorithm to optimize TLC separation. J. Planar Chromat. 2005; 18: 112-117. Jian JH, Wang JH, Song XH, Yu RQ. Network training and architecture optimization by a recursive approach and modified genetic algorithm. J. Chemometr. 1996; 10: 253-267. Wang J, Xian R, Yang B, Wang D, Wang Y, Chen S. Application of genetic algorithm-spectrophotometric method for the multicomponent simultaneous determination of rare earth elements in geological samples. Fenxi Huazue 1999; 27: 955-956. Bhatti MS, Kapoor D, Kalia RK, Reddy AS, Thukral AK. RSM and ANN modeling for electrocoagulation of copper from simulated wastewater; multi objective optimization using genetic algorithm approach. Desalination 2011; 274: 74-80. Csefalvayova L, Pelikan M, Kralj Cigic I, Kolar J, Strli M. Use of genetic algorithms with multivariate regression for determination of gelatine in historic papers based on FT-IR and NIR spectral data. Talanta 2010; 82: 1784-1790. Goodarzi M, Freitas MP, Wu CH, Duchowicz PR. pKa modeling and prediction of series of pH indicators through genetic algorithm-least square support vector regression. Chemometr. Intell. Lab 2010; 101: 102-109. Liu F, Wang JD. Using genetic algorithm for quantitative analysis of overlapped spectra in FTIR spectra. Spectroscopy Spectral Anal. 2001; 21: 609-610. Ghavami R, Najafi A, Sajadi M, Djannaty F. Genetic algorithm as variable selection procedure for the simulation of 13 C nuclear magnetic resonance spectra of flavonoid derivatives using multiple linear regression. J. Mol. Graph. Model. 2008; 27: 105-115. Guruprasad R, Behera BK. Genetic algorithms and its application to textile. Textile Asia 2009; 40: 35-38. Ghasemi J, Ebrahimi DM, Hejazi L, Leardi R, Niazi A. Simultaneous kinetic-spectrophotometric determination of sulfide and sulfite by partial least squares and genetic algorithms variable selection. J. Anal. Chem. 2007; 62: 348-354. Carneiro RL, Braga JWB, Bottoli CBG, Poppi RJ. Application of genetic algorithm for selection of variables for the BLLS method applied to determination of pesticides and metabolites in wine. Anal. Chim. Acta 2007; 595: 51-58. Niazi A, Soufi A, Mobarakabadi M. Genetic algorithm applied to selection of wavelength in partial least squares for simultaneous spectrophotometric determination of nitrophenol isomers. Anal. Lett. 2006; 39: 2359-2372. Vandeginste BGM, Massart DL, Buydens LMC, De Long S, Lewi PJ, Smeyers-Verbeke J. Handbook of Chemometrics and Qualimetrics, Part B. Elsevier Science: Amsterdam, 1998. Luke BT. Genetic algorithms and beyond. Data Handl. Sci. Techn. 2003; 23: 3-54. Hemmateenejad B, Miri R, Akhond M, Shamsipur M. QSAR study of the calcium channel antagonist activity of some recently synthesized dihydropyridine derivatives: an application of genetic algorithm for variable selection in MLR and PLS methods. Chemometr. Intell. Lab 2002; 64: 91-99. Van Kampen AHC, Buydens LMC, Lucasius, CB, Blommers MJJ. Optimization of metric matrix embedding by genetic algorithms. J. Biomol. 1996; 7: 214-224. Niesse JA, Mayne HR. global optimization of atomic and molecular clusters using the space-fixed modified genetic algorithm method. J. Comput. Chem. 1997; 18: 1233-1244. Jalali-Heravi M, Kyani A. Application of genetic algorithm-kernel partial least squares as a novel nonlinear feature selection method: activity of carbonic anhydrase II inhibitors. Eur. J. Med. Chem. 2007; 45: 649-659. Wold S, Trygg J, Berglund A, Antii H. Some recent developments in PLS mg. Chemometr. Intell. Lab 2001; 58: 131-151. Lucasius CB, Beckers MLM, Kateman G. Genetic algorithms in wavelength selection: a comparative study. Anal. Chim. Acta 1994; 286: 135-153. Majidi MR, Jouyban A, Asadpour-Zeynali K. Genetic algorithm based potential selection in simultaneous voltammetric determination of isoniazid and hydrazine by using partial least squares and artificial neural networks. Electroanalysis 2005; 17: 915-918. Kompany-Zareh M, Farrokhi-Kurd S. Genetic algorithm applied to the selection of conditions for the simultaneous quantification of three-food colorants using a hand scanner. Microchim. Acta 2005; 150: 77-85. Massart DL, Vandeginste BGM, Buydens LMC, De Long S, Lewi PJ, Smeyers-Verbeke J. Handbook of Chemometrics and Qualimetrics, Part A. Elsevier Science: Amsterdam, 1997. Abdollahi H, Bagheri L. Simultaneous spectrophotometric of p-benzoquinone and chloranil after microcrystalline naphthalene extraction using genetic algorithm-based wavelength selection-partial least squares regression. Anal. Sci. 2004; 20: 1701-1706. Lucasius CB, Kateman G. Genetic algorithms for large-scale optimization in chemometrics: an application. Trends Anal. Chem. 1991; 10: 254-261. Hanger J, Huttner G. Optimization and analysis of force field parameters by combination genetic algorithms and neural networks. J. Comput. Chem. 1999; 20: 455-471. Dods J, Gruner D, Brumer P. A genetic algorithm approach to fitting polyatomic spectra via geometry shifts. Chem. Phys. Lett. 1996; 261: 612-619. Sadi M, Dabir B. Application of genetic algorithm to determine kinetic parameters of free radical polymerization of vinyl acetate by multi-objective optimization technique. Iran. J. Chem. Chem. Eng. 2007; 26: 29-37. Zou X, Zhao J, Mao H, Shi J, Yin X, Li Y. Genetic algorithm interval partial least squares regression combined successive projection algorithm for variable selection in near-infrared quantitative analysis of pigment in cucumber leaves. Appl. Spectrosc. 2010; 64: 786-794. Kompany-Zareh M, Mirzaei M. Genetic algorithm-based method for selection conditions in multivariate determination of povidone-iodine using hand scanner. Anal. Chim. Acta 2004; 521: 231-236. Horchner U, Kalivas JH. Further investigation on a comparative study on simulated annealing and genetic algorithm for wavelengths selection. Anal. Chim. Acta 1995; 311: 1-13. Tominaga Y. Representative subset selection using genetic algorithms. Chemometr. Intell. Lab 1998; 43: 157-163. Lestander TA, Leardi R, Geladi P. Selection of near infrared wavelengths using genetic algorithms for the determination of seed moisture content. J. Near Infrared Spec. 2003; 11: 433-446. Smith BM, Gemperline PJ. Wavelength selection and optimization of pattern recognition methods using the genetic algorithm. Anal. Chim. Acta 2000; 423: 167-177. Vadood M, Semnani D, Morshed M. Optimization of acrylic dry spinning production line by using artificial neural network and genetic algorithm. J. Appl. Polym. Sci. 2011; 120: 735-744. Roger JM, Bellon-Maurel V. Using genetic algorithms to select wavelengths in near-infrared spectra: application to sugar content prediction in cherries. Appl. Spectrosc. 2000; 59: 1313-1320. Frost VJ, Molt K. Use of genetic algorithm for factor selection in principal component regression. J. Near Infrared Spec. 1998; 6: A185-A190. Chen K, Li T, Lu P. Application of genetic algorithms in resolution of chromatogram. Fenxi Huaxue 2003; 31: 158-162. Guo W, Cai W, Shao X, Pan Z. Application of genetic stochastic resonance algorithm to quantitative structure-activity relationship study. Chemometr. Intell. Lab 2005; 75: 181-188. Arakawa M, Yamashita Y, Funatsu K. Genetic algorithm-based wavelength 2004; 20 2006; 30 1991; 10 1995; 34 2006; 39 2010; 101 2006; 36 1999; 46 1996; 261 1975 1999; 45 1994; 66 2003; 59 1995; 376 2003; 50 2009; 114 1992; 6 1998; 17 2011; 366 2010; 26 2006; 20 2009; 97 2000; 14 2008; 27 2005; 75 2007; 62 1999; 50 2001; 58 2006; 562 2003; 43 2011; 120 1999; 27 1995; 55 1998 1997 1996 1995 1999; 20 1995; 311 2007; 97 1998; 253 1996; 10 2003; 31 1999 2001; 21 2001; 446 1994; 286 2003; 622 2002; 63 2002; 64 2006; 46 1999; 39 2002; 366 1998; 70 2007; 85 1998; 6 2001; 34 2005; 17 2005; 18 1998; 9 2003; 23 2009; 45 2011; 158 2009; 40 2004; 521 2000; 43 2003; 17 1998; 41 1996; 35 1998; 43 2008; 71 2003; 11 2005; 24 2011; 274 2010; 64 1997; 348 2004; 70 2002; 461 2000; 59 2002; 45 1995; 67 2002; 106 1997; 18 1997; 17 2008; 67 2001; 15 2011; 25 2003; 486 2007; 26 1996; 7 2010; 76 2005; 150 1997; 69 2007 1993; 261 1999; 388 2011; 690 2005; 45 2010; 82 1998; 38 1993; 19 2004; 18 2004; 16 2000; 423 2007; 595 2007; 1158 1993; 97 2000; 40 2011; 49 2004; 514 2007; 45 2003; 65 2003; 67 e_1_2_7_108_1 e_1_2_7_104_1 e_1_2_7_127_1 e_1_2_7_7_1 e_1_2_7_19_1 e_1_2_7_60_1 e_1_2_7_83_1 e_1_2_7_100_1 e_1_2_7_123_1 e_1_2_7_15_1 e_1_2_7_41_1 e_1_2_7_87_1 e_1_2_7_11_1 e_1_2_7_45_1 e_1_2_7_68_1 Judson RS (e_1_2_7_29_1) 1997 e_1_2_7_26_1 e_1_2_7_49_1 Massart DL (e_1_2_7_5_1) 1997 Hou T (e_1_2_7_25_1) 2004; 16 e_1_2_7_116_1 e_1_2_7_90_1 e_1_2_7_112_1 e_1_2_7_94_1 e_1_2_7_71_1 e_1_2_7_52_1 e_1_2_7_23_1 e_1_2_7_33_1 e_1_2_7_75_1 e_1_2_7_56_1 e_1_2_7_37_1 e_1_2_7_79_1 Sadi M (e_1_2_7_126_1) 2007; 26 e_1_2_7_109_1 Hou TJ (e_1_2_7_53_1) 1998; 9 Guruprasad R (e_1_2_7_128_1) 2009; 40 e_1_2_7_105_1 e_1_2_7_8_1 Liu F (e_1_2_7_92_1) 2001; 21 e_1_2_7_101_1 e_1_2_7_16_1 e_1_2_7_40_1 e_1_2_7_82_1 Chen K (e_1_2_7_98_1) 2003; 31 e_1_2_7_63_1 e_1_2_7_12_1 e_1_2_7_44_1 e_1_2_7_86_1 e_1_2_7_67_1 Fatemi S (e_1_2_7_124_1) 2005; 24 e_1_2_7_48_1 Niazi A (e_1_2_7_66_1) 2006; 30 Devillers J (e_1_2_7_28_1) 1996 e_1_2_7_117_1 Holland JH (e_1_2_7_2_1) 1975 e_1_2_7_113_1 e_1_2_7_51_1 e_1_2_7_70_1 e_1_2_7_93_1 e_1_2_7_24_1 e_1_2_7_32_1 e_1_2_7_55_1 e_1_2_7_74_1 e_1_2_7_97_1 e_1_2_7_20_1 e_1_2_7_36_1 e_1_2_7_59_1 e_1_2_7_78_1 Mitchell M (e_1_2_7_3_1) 1999 e_1_2_7_106_1 Kompany‐Zareh M (e_1_2_7_64_1) 2003; 50 e_1_2_7_9_1 e_1_2_7_102_1 e_1_2_7_125_1 e_1_2_7_17_1 e_1_2_7_62_1 e_1_2_7_81_1 e_1_2_7_121_1 e_1_2_7_13_1 e_1_2_7_43_1 e_1_2_7_85_1 e_1_2_7_47_1 Otto M (e_1_2_7_4_1) 2007 e_1_2_7_118_1 e_1_2_7_114_1 e_1_2_7_73_1 e_1_2_7_110_1 e_1_2_7_50_1 e_1_2_7_31_1 e_1_2_7_77_1 e_1_2_7_54_1 e_1_2_7_96_1 e_1_2_7_21_1 e_1_2_7_35_1 Kariuki BM (e_1_2_7_120_1) 1998; 38 e_1_2_7_58_1 e_1_2_7_39_1 Vandeginste BGM (e_1_2_7_6_1) 1998 Wang J (e_1_2_7_89_1) 1999; 27 e_1_2_7_107_1 e_1_2_7_80_1 e_1_2_7_103_1 e_1_2_7_18_1 e_1_2_7_84_1 e_1_2_7_122_1 e_1_2_7_61_1 e_1_2_7_14_1 e_1_2_7_42_1 e_1_2_7_88_1 e_1_2_7_65_1 e_1_2_7_10_1 e_1_2_7_46_1 e_1_2_7_69_1 e_1_2_7_27_1 e_1_2_7_119_1 e_1_2_7_91_1 e_1_2_7_115_1 e_1_2_7_72_1 e_1_2_7_95_1 e_1_2_7_111_1 e_1_2_7_30_1 e_1_2_7_76_1 e_1_2_7_99_1 e_1_2_7_22_1 e_1_2_7_34_1 e_1_2_7_57_1 e_1_2_7_38_1 |
| References_xml | – reference: Shaffer RE, Small GW. Learning optimization from nature: simulated annealing and genetic algorithms. Anal. Chem. 1997; 69: 236A-242A. – reference: Riahi S, Ganjali MR, Pourbasheer E, Norouzi P. QSPR study of GC retention indices of essential oil compounds by multiple linear regression with a genetic algorithm. Chromatographia 2008; 67: 917-922. – reference: Chedly S, Chettah A, Ichchou MN. Multiobjective optimization of molded LDPE foams characteristics using genetic algorithm. J. Appl. Ploym. Sci. 2009; 114: 358-368. – reference: Hervas C. Algar JA, Silva M. Correction of temperature variations in kinetic-based determinations by use of pruning computational neural networks in conjucation with gentic algorithms. J. Chem. Inf. Comp. Sci. 2000; 40: 724-731. – reference: Jouan-Rimbaud D, Massart DL, De Noord OE. Random correlation in variable selection for multivariate calibration with a genetic algorithm. Chemometr. Intell. Lab 1996; 35: 213-220. – reference: Yoshida H, Leardi R, Funatsu K, Varmuza K. Feature selection by genetic algorithms for mass spectral classifiers. Anal. Chim. Acta 2001; 446: 485-494. – reference: Luke BT. Applying genetic algorithms and neural networks to chemometric problems. Data Handl. Sci. Techn. 2003; 23: 343-375. – reference: Vadood M, Semnani D, Morshed M. Optimization of acrylic dry spinning production line by using artificial neural network and genetic algorithm. J. Appl. Polym. Sci. 2011; 120: 735-744. – reference: Luke BT. Genetic algorithms and beyond. Data Handl. Sci. Techn. 2003; 23: 3-54. – reference: Lucasius CB, Beckers MLM, Kateman G. Genetic algorithms in wavelength selection: a comparative study. Anal. Chim. Acta 1994; 286: 135-153. – reference: Acros MJ, Alonso C, Ortiz MC. Genetic-algorithm-based potential selection in multivariate voltammetric determination of idomethacin and acemethacin by partial least squares. Electrochim. Acta 1998; 43: 479-485. – reference: Guo W, Cai W, Shao X, Pan Z. Application of genetic stochastic resonance algorithm to quantitative structure-activity relationship study. Chemometr. Intell. Lab 2005; 75: 181-188. – reference: Shi J, Xue X. Optimization design of electrodes for anode-supported solid oxide fuel cells via genetic algorithm. J. Electrochem. Soc. 2011; 158: B143-B151. – reference: Wold S, Trygg J, Berglund A, Antii H. Some recent developments in PLS mg. Chemometr. Intell. Lab 2001; 58: 131-151. – reference: Chen XG, Li X, Kong L, Ni JY, Zhao RH, Zou HF. Application of uniform design and genetic algorithm in optimization of reversed-phase chromatographic separation. Chemometr. Intell. Lab 2003; 67: 157-166. – reference: Kompany-Zareh M, Farrokhi-Kurd S. Genetic algorithm applied to the selection of conditions for the simultaneous quantification of three-food colorants using a hand scanner. Microchim. Acta 2005; 150: 77-85. – reference: Wehrens R, Prestsch E, Buydens LMC. The quality of optimization by genetic algorithms. Anal. Chim. Acta 1999; 388: 265-271. – reference: Lavin BK, Moores A, Helfend LK. Genetic algorithm for pattern recognition analysis of pyrolysis gas chromatographic data. J. Anal. Appl. Pyrol. 1999; 50: 47-62. – reference: Broudiscou A, Leardi R, Phan-Tan-Luu R. Genetic algorithm as a tool for selection of D-optimal design. Chemometr. Intell. Lab 1996; 35: 105-116. – reference: Wang J, Xian R, Yang B, Wang D, Wang Y, Chen S. Application of genetic algorithm-spectrophotometric method for the multicomponent simultaneous determination of rare earth elements in geological samples. Fenxi Huazue 1999; 27: 955-956. – reference: Hou TJ, Wang JM, Liao N, Xu XJ. Applications of genetic algorithms on the structure-activity relationship analysis of some cinnamamides. J. Chem. Inf. Comp. Sci. 1999; 39: 775-781. – reference: Hemmateenejad B, Akhond M, Miri R, Shamsipur M. Genetic algorithm applied to the selection of factors in principal component-artificial neural networks: application to QSAR study of calcium channel antagonist activity of 1,4-dihydropyridines. J. Chem. Inf. Comp. Sci. 2003; 43: 1328-1334. – reference: Yu K, Lin Z, Cheng Y. optimization of the buffer system of micellar electrokinetic capillary chromatography for the separation of the active components in Chinese medicine 'SHUANGDAN' granule by genetic algorithm. Anal. Chim. Acta 2006; 562: 66-72. – reference: Bhatti MS, Kapoor D, Kalia RK, Reddy AS, Thukral AK. RSM and ANN modeling for electrocoagulation of copper from simulated wastewater; multi objective optimization using genetic algorithm approach. Desalination 2011; 274: 74-80. – reference: Dieterle F, Kieser B, Gauglitz G. Genetic algorithms and neural networks for quantitative analysis of ternary mixtures using surface plasmon resonance. Chemometr. Intell. Lab 2003; 65: 67-81. – reference: Leardi R, Seasholtz MB, Pell RJ. Variable selection for multivariate calibration using a genetic algorithm: prediction of additive concentrations in polymer films from Fourier transform-infrared spectral data. Anal. Chim. Acta 2002; 461: 189-200. – reference: Lucasius CB, Kateman G. Understanding and using genetic algorithms. Part 1: concepts, properties and context. Chemometr. Intell. Lab 1993; 19: 1-33. – reference: Abdollahi H, Bagheri L. Simultaneous spectrophotometric of p-benzoquinone and chloranil after microcrystalline naphthalene extraction using genetic algorithm-based wavelength selection-partial least squares regression. Anal. Sci. 2004; 20: 1701-1706. – reference: Leardi R. Genetic algorithms in chemistry. J. Chromatogr. A 2007; 1158: 226-233. – reference: Kompany-Zareh M. A QSPR study of boiling point of saturated alcohols using genetic algorithm. Acta Chim. Slov. 2003; 50: 259-273. – reference: Dane AD, Veldusi A, de Beer DKG, Leenaers AJG, Buydens LMC. Application of genetic algorithms for characterization of thin layer materials by glancing incidence X-ray refractometry. Physica B 1998; 253: 254-268. – reference: Jouan-Rimbaud D, Massart DL, Leardi R, De Noord OE. Genetic algorithms as a tool for wavelength selection in multivariate calibration. Anal. Chem. 1995; 67: 4295-4301. – reference: Hou TJ, Wang JM, Xu XJ. Applications of genetic algorithms on the structure-activity correlation study of a group of nin-nucleoside HIV-1 inhibitors. Chemometr. Intell. Lab 1999; 45: 303-310. – reference: Ghasemi J, Ebrahimi DM, Hejazi L, Leardi R, Niazi A. Simultaneous kinetic-spectrophotometric determination of sulfide and sulfite by partial least squares and genetic algorithms variable selection. J. Anal. Chem. 2007; 62: 348-354. – reference: Weber L, Wallbaum S, Broger C, Gubernator K. Optimization of the biological activity of combinatorial compound libraries by a genetic algorithm. Angew. Chem. 1995; 34: 2280-2282. – reference: Devillers J. Genetic Algorithms in Molecular Modeling. Principles of QSAR and Drug Design. Academic Press: New York, 1996. – reference: Niesse JA, Mayne HR. global optimization of atomic and molecular clusters using the space-fixed modified genetic algorithm method. J. Comput. Chem. 1997; 18: 1233-1244. – reference: Gianoli SI, Puxty G, Fisher U, Maeder M, Hungerbuchler K. Empirical kinetic modeling of on line simultaneous infrared and calorimetric measurement using a Pareto optimal approach and multi-objective genetic algorithm. Chemometr. Intell. Lab 2007; 85: 47-62. – reference: Guruprasad R, Behera BK. Genetic algorithms and its application to textile. Textile Asia 2009; 40: 35-38. – reference: Frost VJ, Molt K. Use of genetic algorithm for factor selection in principal component regression. J. Near Infrared Spec. 1998; 6: A185-A190. – reference: Reynes C, De Souza S, Sabatier R, Figueres G, Vidal B. Selection of discriminant wavelength intervals in NIR spectrometry with genetic algorithms. J. Chemometr. 2006; 20: 136-145. – reference: Hanger J, Huttner G. Optimization and analysis of force field parameters by combination genetic algorithms and neural networks. J. Comput. Chem. 1999; 20: 455-471. – reference: Forrest S. Genetic algorithms: principles of natural selection applied to computation. Science 1993; 261: 872-878. – reference: Abdollahi H, Bagheri L. Simultaneous spectrophotometric determination of vitamin K3 and 1,4-naphthoquinone after cloud point extraction by using genetic algorithm based wavelength selection-partial least squares regression. Anal. Chim. Acta 2004; 514: 211-218. – reference: Leardi R, Boggia R, Terrile M. Genetic algorithms as a strategy for feature selection. J. Chemometr. 1992; 6: 267-281. – reference: Liu F, Wang JD. Using genetic algorithm for quantitative analysis of overlapped spectra in FTIR spectra. Spectroscopy Spectral Anal. 2001; 21: 609-610. – reference: Goicoechea HC, Olivieri AC. A new family of genetic algorithms for wavelength interval selection in multivariate analytical spectroscopy. J. Chemometr. 2003; 17: 338-345. – reference: Horchner U, Kalivas JH. Further investigation on a comparative study on simulated annealing and genetic algorithm for wavelengths selection. Anal. Chim. Acta 1995; 311: 1-13. – reference: Massart DL, Vandeginste BGM, Buydens LMC, De Long S, Lewi PJ, Smeyers-Verbeke J. Handbook of Chemometrics and Qualimetrics, Part A. Elsevier Science: Amsterdam, 1997. – reference: Tominaga Y. Representative subset selection using genetic algorithms. Chemometr. Intell. Lab 1998; 43: 157-163. – reference: De Weijer AP, Lucasius CB, Buydens LMC, Kateman G, Heuvel HM, Mannee H. Curve fitting using natural computation. Anal. Chem. 1994; 66: 23-31. – reference: Clark DE, Westhead DR. Evolutionary algorithms in computer-aided molecular design. J. Comput. Aid. Mol. Des. 1996; 10: 337-358. – reference: Van Kampen AHC, Buydens LMC, Lucasius, CB, Blommers MJJ. Optimization of metric matrix embedding by genetic algorithms. J. Biomol. 1996; 7: 214-224. – reference: Gabrielsson J, Trygg J. Recent developments in multivariate calibration. Crit. Rev. Anal. Chem. 36; 2006: 243-255. – reference: Niculescu SP. Artificial neural networks and genetic algorithms in QSAR. J. Mol. Struct. (THEOCHEM) 2003; 622: 71-83. – reference: Csefalvayova L, Pelikan M, Kralj Cigic I, Kolar J, Strli M. Use of genetic algorithms with multivariate regression for determination of gelatine in historic papers based on FT-IR and NIR spectral data. Talanta 2010; 82: 1784-1790. – reference: Mitchell M. An introduction to genetic algorithms. The MIT Press, Massachusetts, 1999. – reference: Goicoechea HC, Olivieri AC. Wavelength selection for multivariate calibration using a genetic algorithm: a novel initialization strategy. J. Chem. Inf. Comp. Sci. 2002; 45: 1146-1153. – reference: Leardi R. Genetic algorithm-PLS as a tool for wavelength selection in spectral data sets. Data Handl. Sci. Techn. 2003; 23: 169-196. – reference: Kabrede H, Hentschke R. An improved genetic algorithm for global optimization and its application to sodium chloride clusters. J. Phys. Chem. B 2002; 106: 10089-10095. – reference: Carneiro RL, Braga JWB, Bottoli CBG, Poppi RJ. Application of genetic algorithm for selection of variables for the BLLS method applied to determination of pesticides and metabolites in wine. Anal. Chim. Acta 2007; 595: 51-58. – reference: Ghasemi J, Niazi A, Leardi R. Genetic-algorithm-based wavelength selection in multicomponent spectrophotometric determination by PLS: application on copper and zinc mixture. Talanta 2003; 59: 311-317. – reference: Fatemi MH, Jalali-Heravi M, Konuze E. Prediction of bioconcentration factor using genetic algorithm and artificial neural network. Anal. Chim. Acta 2003; 486: 101-108. – reference: Meusinger R, Moros R. Determination of quantitative structure-octane rating relationships of hydrocarbons by genetic algorithms. Chemometr. Intell. Lab 1999; 46: 67-78. – reference: Benedetti G, Morosetti S. A genetic algorithm to search for optimal and suboptimal RNA secondary structures. Biophys. Chem. 1995; 55: 253-259. – reference: Hemmateenejad B, Miri R, Akhond M, Shamsipur M. QSAR study of the calcium channel antagonist activity of some recently synthesized dihydropyridine derivatives: an application of genetic algorithm for variable selection in MLR and PLS methods. Chemometr. Intell. Lab 2002; 64: 91-99. – reference: Hemmateenejad B. Optimal QSAR analysis of the carcinogenic activity of drugs by correlation ranking and gentic algorithm-based PCR. J. Chemometr. 2004; 18: 475-485. – reference: Sadi M, Dabir B. Application of genetic algorithm to determine kinetic parameters of free radical polymerization of vinyl acetate by multi-objective optimization technique. Iran. J. Chem. Chem. Eng. 2007; 26: 29-37. – reference: Kemsley EK. A genetic algorithm (GA) approach to the calculation of canonical variates. Trends Anal. Chem. 1998; 17: 24-34. – reference: Afiuni-Zadeh S, Azimi G. A QSAR for modeling of 8-azaadenine analogues proposed as Al adenosine receptor antagonists using genetic algorithm coupling adaptive neuro-fuzzy inference system. Anal. Sci. 2010; 26: 897-902. – reference: Hibbert DB. Hybrid genetic algorithms. Data Handl. Sci. Techn. 2003; 23: 55-68. – reference: Ghavami R, Najafi A, Sajadi M, Djannaty F. Genetic algorithm as variable selection procedure for the simulation of 13 C nuclear magnetic resonance spectra of flavonoid derivatives using multiple linear regression. J. Mol. Graph. Model. 2008; 27: 105-115. – reference: Madaeni SS, Hasankiadeh NT, Kurdian AR, Rahipour A. Modeling and optimization of membrane fabrication using artificial neural network and genetic algirthm. Sep. Purif. Technol. 2010; 76: 33-43. – reference: Zupan J, Novic M. General type of a uniform and reversible representation of chemical structures. Anal. Chim. Acta 1997; 348: 409-418. – reference: Zou X, Zhao J, Mao H, Shi J, Yin X, Li Y. Genetic algorithm interval partial least squares regression combined successive projection algorithm for variable selection in near-infrared quantitative analysis of pigment in cucumber leaves. Appl. Spectrosc. 2010; 64: 786-794. – reference: Roger JM, Bellon-Maurel V. Using genetic algorithms to select wavelengths in near-infrared spectra: application to sugar content prediction in cherries. Appl. Spectrosc. 2000; 59: 1313-1320. – reference: Brodhurst D, Goodacre R, Jones A, Rowland JJ, Kell DB. Genetic algorithms as a method for variable selection in multiple linear regression and partial least squares regression. Anal. Chim. Acta 1997; 348: 71-86. – reference: Ding Q, Small GW, Arnold MA. Genetic algorithm-based wavelength selection for the near-infrared determination of glucose in biological matrixes: initialization strategies and effects of spectral resolution. Anal. Chem. 1998; 70: 4472-4479. – reference: Gharagheizi F. QSPR studies for solubility parameter by means of genetic algorithm-based multivariate linear regression and generalized regression neural network. QSAR Comb. Sci. 2008; 27: 165-170. – reference: Harris KDM. Fundamentals and applications of genetic algorithms for structure solution from powder X-ray diffraction data. Comp. Mat. Sci. 2009; 45: 16-20. – reference: Chen K, Li T, Lu P. Application of genetic algorithms in resolution of chromatogram. Fenxi Huaxue 2003; 31: 158-162. – reference: Liu F, Wang JD. Application of a genetic algorithm to quantitative analysis of overlapped FTIR spectra. Spectrosc. Lett. 2001; 34: 13-24. – reference: Ghasemi J, Ahmadi S. Combination of genetic algorithm and partial least squares for cloud point prediction of nonionic surfactants from molecular structures. Ann. Chim. 2007; 97: 69-83. – reference: Hou T, Xu X. Applications of genetic algorithms to computer-aided drug design. Prog. Chem. 2004; 16: 35-41. – reference: Maeder M, Neuhold YM, Puxty G. Applications of a genetic algorithm: near optimal estimation of the rate and equilibrium constants of complex reaction mechanism. Chemometr. Intell. Lab 2004; 70: 193-203. – reference: Maiocchi A. Genetic algorithms in molecular modeling: a review. Data Handl. Sci. Techn. 2003; 23: 109-139. – reference: Lucasius CB, Kateman G. Genetic algorithms for large-scale optimization in chemometrics: an application. Trends Anal. Chem. 1991; 10: 254-261. – reference: Giro R, Cyrillo M, Galvao DS. Designing conducting polymers using genetic algorithms. Chem. Phys. Lett. 2002; 366: 170-175. – reference: Cano-Odena A, Spilliers M, Dedroog T, De Grave K, Raman J, Vankelecom IFJ. Optimization of cellulose acetate nanaofilteration membrane for micropollutant removal via genetic algorithms and high throughout experimentation. J. Membrane Sci. 2011; 366: 25-32. – reference: Tewari JC, Dixit V, Cho BK, Malik KA. Detemination of origin and sugars of citrus fruits using genetic algorithm, correspondence analysis and partial least square combined with fiber optic NIR spectroscopy. Spectrochim. Acta A 2008; 71: 1119-1127. – reference: Maddox J. Genetics helping molecular dynamics. Nature 1995; 376: 209. – reference: Jalali-Heravi M, Kyani A. Application of genetic algorithm-kernel partial least squares as a novel nonlinear feature selection method: activity of carbonic anhydrase II inhibitors. Eur. J. Med. Chem. 2007; 45: 649-659. – reference: Niazi A, Soufi A, Mobarakabadi M. Genetic algorithm applied to selection of wavelength in partial least squares for simultaneous spectrophotometric determination of nitrophenol isomers. Anal. Lett. 2006; 39: 2359-2372. – reference: Hao, M, Li Y, Wang Y, Zhang S. Prediction of P2Y12 antagonists using a novel genetic algorithm-support vector machine coupled approach. Anal. Chim. Acta 2011; 690: 56-63. – reference: Milani G, Milani F. EPDM accelerated sulfur vulcanization: A kinetic model based on a genetic algorithm. J. Math. Chem. 2011; 49: 1357-1383. – reference: Jian JH, Wang JH, Song XH, Yu RQ. Network training and architecture optimization by a recursive approach and modified genetic algorithm. J. Chemometr. 1996; 10: 253-267. – reference: Zinn P, Adaptive multicomponent analysis by genetic algorithms. J. Chem. Inf. Model. 2005; 45: 880-887. – reference: Kariuki BM, Johnston RL, Harris KDM, Psallidas K, Ahn S, Serrano-Gonzalez H. Application of a genetic algorithm in structure determination from powder diffraction data. Match 1998; 38: 123-135. – reference: Goodarzi M, Freitas MP, Wu CH, Duchowicz PR. pKa modeling and prediction of series of pH indicators through genetic algorithm-least square support vector regression. Chemometr. Intell. Lab 2010; 101: 102-109. – reference: Wehrens R, Buydens LMC. Evolutionary optimization: a tutorial. Trends Anal. Chem. 1997; 17: 193-203. – reference: Babic S, Horvat AJM, Kastelan-Macan M. Use of a genetic algorithm to optimize TLC separation. J. Planar Chromat. 2005; 18: 112-117. – reference: Holland JH. Adaptation in Natural and Artificial Systems. The University of Michigan Press, Michigan, 1975. – reference: Dods J, Gruner D, Brumer P. A genetic algorithm approach to fitting polyatomic spectra via geometry shifts. Chem. Phys. Lett. 1996; 261: 612-619. – reference: Fei Q, Li M, Wang B, Huan Y, Feng G, Ren Y. Analysis of cefalexin with NIR spectrometry coupled to artificial neural networks with modified genetic algorithm for wavelength selection. Chemometr. Intell. Lab 2009; 97: 127-131. – reference: Meusinger R, Himmelreich U. Neural networks and genetic algorithms applications in nuclear magnetic resonance spectroscopy. Data Handl. Sci. Techn. 2003; 23: 281-321. – reference: Otto M. Chemometrics. Wiely-VCH Verlag GmbH and Co.: Weinheim, 2007. – reference: Leardi R. Application of genetic algorithm-PLS for feature selection in spectral data sets. J. Chemometr. 2000; 14: 643-655. – reference: Fatemi S, Masoori M, Bozorgmehry Boozarjomehry R. Application of genetic algorithm in kinetic modeling and reaction mechanism studies. Iran. J. Chem. Chem. Eng. 2005; 24: 37-46. – reference: Hoffman BT, Kopajtic T, Katz JL, Newman AH. 2D QSAR modeling and preliminary database searching for dopamine transporter inhibitors using genetic algorithm variable selection of Molconn Z descriptors. J. Med. Chem. 2000; 43: 4151-4159. – reference: Smith BM, Gemperline PJ. Wavelength selection and optimization of pattern recognition methods using the genetic algorithm. Anal. Chim. Acta 2000; 423: 167-177. – reference: Kompany-Zareh M, Mirzaei M. Genetic algorithm-based method for selection conditions in multivariate determination of povidone-iodine using hand scanner. Anal. Chim. Acta 2004; 521: 231-236. – reference: Hou TJ, Wang JM, Li YY, Xu XY. Application of genetic algorithm to the QSAR research of pyrrolobenzothiazepinones and pyrrolobenzoxazepinone-novel and specific non-nucleoside HIV-1 reverse transcription inhibitors. Chin. Chem. Lett. 1998; 9: 651-654. – reference: Leardi R, Lupianez Gonzalez A. Genetic algorithm applied to feature selection in PLS regression: How and when to use them. Chemometr. Intell. Lab 1998; 41: 195-207. – reference: Arakawa M, Yamashita Y, Funatsu K. Genetic algorithm-based wavelength selection method for spectral calibration. J. Chemometr. 2011; 25: 10-19. – reference: Majidi MR, Jouyban A, Asadpour-Zeynali K. Genetic algorithm based potential selection in simultaneous voltammetric determination of isoniazid and hydrazine by using partial least squares and artificial neural networks. Electroanalysis 2005; 17: 915-918. – reference: Hibbert DB. Ahybrid genetic algorithm for the estimation of kinetic parameters. Chemometr. Intell. Lab 1993; 19: 319-329. – reference: Leardi R. Genetic algorithms in chemometrics and chemistry: a review. J. Chemometr. 2001; 15: 559-569. – reference: Vandeginste BGM, Massart DL, Buydens LMC, De Long S, Lewi PJ, Smeyers-Verbeke J. Handbook of Chemometrics and Qualimetrics, Part B. Elsevier Science: Amsterdam, 1998. – reference: Hibbert DB. Genetic algorithms in chemistry. Chemometr. Intell. Lab 1993; 19: 277-293. – reference: Hartke B. Global geometry optimization of clusters using genetic algorithms. J. Phys. Chem. 1993; 97: 9973-9976. – reference: Ros F, Pintore M, Chretien JR. Molecular descriptor selection combining genetic algorithms and fuzzy logic: application to database mining procedure. Chemometr. Intell. Lab 2002; 63: 15-26. – reference: Lestander TA, Leardi R, Geladi P. Selection of near infrared wavelengths using genetic algorithms for the determination of seed moisture content. J. Near Infrared Spec. 2003; 11: 433-446. – reference: Niazi A, Jameh-Bozorghi S, Nori-Shargh D. Prediction of acidity constants of thiazolidine-4-carbozylic acid derivatives using Ab initio and genetic algorithm-partial least squares. Turk. J. Chem. 2006; 30: 619-628. – reference: Wang J, Krudy G, Xie XQ, Wu C, Holland G. Genetic algorithm-optimized QSPR model for bioavailability, protein binding, and urinary excretion. J. Chem. Inf. Model. 2006; 46: 2674-2683. – volume: 18 start-page: 112 year: 2005 end-page: 117 article-title: Use of a genetic algorithm to optimize TLC separation publication-title: J. Planar Chromat. – volume: 120 start-page: 735 year: 2011 end-page: 744 article-title: Optimization of acrylic dry spinning production line by using artificial neural network and genetic algorithm publication-title: J. Appl. Polym. Sci. – volume: 40 start-page: 724 year: 2000 end-page: 731 article-title: Correction of temperature variations in kinetic‐based determinations by use of pruning computational neural networks in conjucation with gentic algorithms publication-title: J. Chem. Inf. Comp. Sci. – volume: 39 start-page: 775 year: 1999 end-page: 781 article-title: Applications of genetic algorithms on the structure‐activity relationship analysis of some cinnamamides publication-title: J. Chem. Inf. Comp. Sci. – volume: 64 start-page: 786 year: 2010 end-page: 794 article-title: Genetic algorithm interval partial least squares regression combined successive projection algorithm for variable selection in near‐infrared quantitative analysis of pigment in cucumber leaves publication-title: Appl. Spectrosc. – volume: 62 start-page: 348 year: 2007 end-page: 354 article-title: Simultaneous kinetic‐spectrophotometric determination of sulfide and sulfite by partial least squares and genetic algorithms variable selection publication-title: J. Anal. Chem. – volume: 366 start-page: 170 year: 2002 end-page: 175 article-title: Designing conducting polymers using genetic algorithms publication-title: Chem. Phys. Lett. – volume: 45 start-page: 303 year: 1999 end-page: 310 article-title: Applications of genetic algorithms on the structure‐activity correlation study of a group of nin‐nucleoside HIV‐1 inhibitors publication-title: Chemometr. Intell. Lab – volume: 82 start-page: 1784 year: 2010 end-page: 1790 article-title: Use of genetic algorithms with multivariate regression for determination of gelatine in historic papers based on FT‐IR and NIR spectral data publication-title: Talanta – year: 1975 – volume: 23 start-page: 343 year: 2003 end-page: 375 article-title: Applying genetic algorithms and neural networks to chemometric problems publication-title: Data Handl. Sci. Techn. – volume: 34 start-page: 13 year: 2001 end-page: 24 article-title: Application of a genetic algorithm to quantitative analysis of overlapped FTIR spectra publication-title: Spectrosc. Lett. – volume: 19 start-page: 1 year: 1993 end-page: 33 article-title: Understanding and using genetic algorithms. Part 1: concepts, properties and context publication-title: Chemometr. Intell. Lab – volume: 43 start-page: 479 year: 1998 end-page: 485 article-title: Genetic‐algorithm‐based potential selection in multivariate voltammetric determination of idomethacin and acemethacin by partial least squares publication-title: Electrochim. Acta – volume: 461 start-page: 189 year: 2002 end-page: 200 article-title: Variable selection for multivariate calibration using a genetic algorithm: prediction of additive concentrations in polymer films from Fourier transform‐infrared spectral data publication-title: Anal. Chim. Acta – volume: 35 start-page: 105 year: 1996 end-page: 116 article-title: Genetic algorithm as a tool for selection of D‐optimal design publication-title: Chemometr. Intell. Lab – volume: 46 start-page: 2674 year: 2006 end-page: 2683 article-title: Genetic algorithm‐optimized QSPR model for bioavailability, protein binding, and urinary excretion publication-title: J. Chem. Inf. Model. – volume: 40 start-page: 35 year: 2009 end-page: 38 article-title: Genetic algorithms and its application to textile publication-title: Textile Asia – volume: 10 start-page: 254 year: 1991 end-page: 261 article-title: Genetic algorithms for large-scale optimization in chemometrics: an application publication-title: Trends Anal. Chem – year: 1998 – volume: 34 start-page: 2280 year: 1995 end-page: 2282 article-title: Optimization of the biological activity of combinatorial compound libraries by a genetic algorithm publication-title: Angew. Chem. – volume: 622 start-page: 71 year: 2003 end-page: 83 article-title: Artificial neural networks and genetic algorithms in QSAR publication-title: J. Mol. Struct. (THEOCHEM) – volume: 64 start-page: 91 year: 2002 end-page: 99 article-title: QSAR study of the calcium channel antagonist activity of some recently synthesized dihydropyridine derivatives: an application of genetic algorithm for variable selection in MLR and PLS methods publication-title: Chemometr. Intell. Lab – volume: 9 start-page: 651 year: 1998 end-page: 654 article-title: Application of genetic algorithm to the QSAR research of pyrrolobenzothiazepinones and pyrrolobenzoxazepinone‐novel and specific non‐nucleoside HIV‐1 reverse transcription inhibitors publication-title: Chin. Chem. Lett. – volume: 46 start-page: 67 year: 1999 end-page: 78 article-title: Determination of quantitative structure‐octane rating relationships of hydrocarbons by genetic algorithms publication-title: Chemometr. Intell. Lab – volume: 18 start-page: 1233 year: 1997 end-page: 1244 article-title: global optimization of atomic and molecular clusters using the space‐fixed modified genetic algorithm method publication-title: J. Comput. Chem. – volume: 348 start-page: 71 year: 1997 end-page: 86 article-title: Genetic algorithms as a method for variable selection in multiple linear regression and partial least squares regression publication-title: Anal. Chim. Acta – volume: 59 start-page: 311 year: 2003 end-page: 317 article-title: Genetic‐algorithm‐based wavelength selection in multicomponent spectrophotometric determination by PLS: application on copper and zinc mixture publication-title: Talanta – volume: 41 start-page: 195 year: 1998 end-page: 207 article-title: Genetic algorithm applied to feature selection in PLS regression: How and when to use them publication-title: Chemometr. Intell. Lab – volume: 50 start-page: 259 year: 2003 end-page: 273 article-title: A QSPR study of boiling point of saturated alcohols using genetic algorithm publication-title: Acta Chim. Slov. – volume: 366 start-page: 25 year: 2011 end-page: 32 article-title: Optimization of cellulose acetate nanaofilteration membrane for micropollutant removal via genetic algorithms and high throughout experimentation publication-title: J. Membrane Sci. – volume: 39 start-page: 2359 year: 2006 end-page: 2372 article-title: Genetic algorithm applied to selection of wavelength in partial least squares for simultaneous spectrophotometric determination of nitrophenol isomers publication-title: Anal. Lett. – volume: 71 start-page: 1119 year: 2008 end-page: 1127 article-title: Detemination of origin and sugars of citrus fruits using genetic algorithm, correspondence analysis and partial least square combined with fiber optic NIR spectroscopy publication-title: Spectrochim. Acta A – volume: 376 start-page: 209 year: 1995 article-title: Genetics helping molecular dynamics publication-title: Nature – volume: 17 start-page: 915 year: 2005 end-page: 918 article-title: Genetic algorithm based potential selection in simultaneous voltammetric determination of isoniazid and hydrazine by using partial least squares and artificial neural networks publication-title: Electroanalysis – year: 2007 – volume: 49 start-page: 1357 year: 2011 end-page: 1383 article-title: EPDM accelerated sulfur vulcanization: A kinetic model based on a genetic algorithm publication-title: J. Math. Chem. – volume: 70 start-page: 4472 year: 1998 end-page: 4479 article-title: Genetic algorithm‐based wavelength selection for the near‐infrared determination of glucose in biological matrixes: initialization strategies and effects of spectral resolution publication-title: Anal. Chem. – volume: 67 start-page: 917 year: 2008 end-page: 922 article-title: QSPR study of GC retention indices of essential oil compounds by multiple linear regression with a genetic algorithm publication-title: Chromatographia – start-page: 35 year: 1996 end-page: 66 – volume: 20 start-page: 136 year: 2006 end-page: 145 article-title: Selection of discriminant wavelength intervals in NIR spectrometry with genetic algorithms publication-title: J. Chemometr. – volume: 15 start-page: 559 year: 2001 end-page: 569 article-title: Genetic algorithms in chemometrics and chemistry: a review publication-title: J. Chemometr. – volume: 562 start-page: 66 year: 2006 end-page: 72 article-title: optimization of the buffer system of micellar electrokinetic capillary chromatography for the separation of the active components in Chinese medicine ‘SHUANGDAN’ granule by genetic algorithm publication-title: Anal. Chim. Acta – volume: 50 start-page: 47 year: 1999 end-page: 62 article-title: Genetic algorithm for pattern recognition analysis of pyrolysis gas chromatographic data publication-title: J. Anal. Appl. Pyrol. – volume: 45 start-page: 1146 year: 2002 end-page: 1153 article-title: Wavelength selection for multivariate calibration using a genetic algorithm: a novel initialization strategy publication-title: J. Chem. Inf. Comp. Sci. – volume: 521 start-page: 231 year: 2004 end-page: 236 article-title: Genetic algorithm‐based method for selection conditions in multivariate determination of povidone‐iodine using hand scanner publication-title: Anal. Chim. Acta – volume: 423 start-page: 167 year: 2000 end-page: 177 article-title: Wavelength selection and optimization of pattern recognition methods using the genetic algorithm publication-title: Anal. Chim. Acta – volume: 35 start-page: 213 year: 1996 end-page: 220 article-title: Random correlation in variable selection for multivariate calibration with a genetic algorithm publication-title: Chemometr. Intell. Lab – volume: 69 start-page: 236A year: 1997 end-page: 242A article-title: Learning optimization from nature: simulated annealing and genetic algorithms publication-title: Anal. Chem. – volume: 31 start-page: 158 year: 2003 end-page: 162 article-title: Application of genetic algorithms in resolution of chromatogram publication-title: Fenxi Huaxue – volume: 45 start-page: 880 year: 2005 end-page: 887 article-title: Adaptive multicomponent analysis by genetic algorithms publication-title: J. Chem. Inf. Model. – volume: 59 start-page: 1313 year: 2000 end-page: 1320 article-title: Using genetic algorithms to select wavelengths in near‐infrared spectra: application to sugar content prediction in cherries publication-title: Appl. Spectrosc. – volume: 19 start-page: 319 year: 1993 end-page: 329 article-title: Ahybrid genetic algorithm for the estimation of kinetic parameters publication-title: Chemometr. Intell. Lab – volume: 24 start-page: 37 year: 2005 end-page: 46 article-title: Application of genetic algorithm in kinetic modeling and reaction mechanism studies publication-title: Iran. J. Chem. Chem. Eng. – year: 1995 – volume: 274 start-page: 74 year: 2011 end-page: 80 article-title: RSM and ANN modeling for electrocoagulation of copper from simulated wastewater; multi objective optimization using genetic algorithm approach publication-title: Desalination – volume: 26 start-page: 897 year: 2010 end-page: 902 article-title: A QSAR for modeling of 8‐azaadenine analogues proposed as Al adenosine receptor antagonists using genetic algorithm coupling adaptive neuro‐fuzzy inference system publication-title: Anal. Sci. – volume: 85 start-page: 47 year: 2007 end-page: 62 article-title: Empirical kinetic modeling of on line simultaneous infrared and calorimetric measurement using a Pareto optimal approach and multi‐objective genetic algorithm publication-title: Chemometr. Intell. Lab – volume: 10 start-page: 337 year: 1996 end-page: 358 article-title: Evolutionary algorithms in computer‐aided molecular design publication-title: J. Comput. Aid. Mol. Des. – volume: 23 start-page: 109 year: 2003 end-page: 139 article-title: Genetic algorithms in molecular modeling: a review publication-title: Data Handl. Sci. Techn. – volume: 388 start-page: 265 year: 1999 end-page: 271 article-title: The quality of optimization by genetic algorithms publication-title: Anal. Chim. Acta – volume: 7 start-page: 214 year: 1996 end-page: 224 article-title: Optimization of metric matrix embedding by genetic algorithms publication-title: J. Biomol. – volume: 486 start-page: 101 year: 2003 end-page: 108 article-title: Prediction of bioconcentration factor using genetic algorithm and artificial neural network publication-title: Anal. Chim. Acta – volume: 6 start-page: A185 year: 1998 end-page: A190 article-title: Use of genetic algorithm for factor selection in principal component regression publication-title: J. Near Infrared Spec. – volume: 17 start-page: 338 year: 2003 end-page: 345 article-title: A new family of genetic algorithms for wavelength interval selection in multivariate analytical spectroscopy publication-title: J. Chemometr. – volume: 17 start-page: 24 year: 1998 end-page: 34 article-title: A genetic algorithm (GA) approach to the calculation of canonical variates publication-title: Trends Anal. Chem. – volume: 23 start-page: 281 year: 2003 end-page: 321 article-title: Neural networks and genetic algorithms applications in nuclear magnetic resonance spectroscopy publication-title: Data Handl. Sci. Techn. – volume: 6 start-page: 267 year: 1992 end-page: 281 article-title: Genetic algorithms as a strategy for feature selection publication-title: J. Chemometr. – volume: 45 start-page: 649 year: 2007 end-page: 659 article-title: Application of genetic algorithm‐kernel partial least squares as a novel nonlinear feature selection method: activity of carbonic anhydrase II inhibitors publication-title: Eur. J. Med. Chem. – volume: 286 start-page: 135 year: 1994 end-page: 153 article-title: Genetic algorithms in wavelength selection: a comparative study publication-title: Anal. Chim. Acta – volume: 27 start-page: 165 year: 2008 end-page: 170 article-title: QSPR studies for solubility parameter by means of genetic algorithm‐based multivariate linear regression and generalized regression neural network publication-title: QSAR Comb. Sci. – volume: 17 start-page: 193 year: 1997 end-page: 203 article-title: Evolutionary optimization: a tutorial publication-title: Trends Anal. Chem. – volume: 23 start-page: 3 year: 2003 end-page: 54 article-title: Genetic algorithms and beyond publication-title: Data Handl. Sci. Techn. – volume: 253 start-page: 254 year: 1998 end-page: 268 article-title: Application of genetic algorithms for characterization of thin layer materials by glancing incidence X‐ray refractometry publication-title: Physica B – volume: 311 start-page: 1 year: 1995 end-page: 13 article-title: Further investigation on a comparative study on simulated annealing and genetic algorithm for wavelengths selection publication-title: Anal. Chim. Acta – volume: 18 start-page: 475 year: 2004 end-page: 485 article-title: Optimal QSAR analysis of the carcinogenic activity of drugs by correlation ranking and gentic algorithm‐based PCR publication-title: J. Chemometr. – volume: 43 start-page: 4151 year: 2000 end-page: 4159 article-title: 2D QSAR modeling and preliminary database searching for dopamine transporter inhibitors using genetic algorithm variable selection of Molconn Z descriptors publication-title: J. Med. Chem. – volume: 20 start-page: 455 year: 1999 end-page: 471 article-title: Optimization and analysis of force field parameters by combination genetic algorithms and neural networks publication-title: J. Comput. Chem. – volume: 446 start-page: 485 year: 2001 end-page: 494 article-title: Feature selection by genetic algorithms for mass spectral classifiers publication-title: Anal. Chim. Acta – volume: 25 start-page: 10 year: 2011 end-page: 19 article-title: Genetic algorithm‐based wavelength selection method for spectral calibration publication-title: J. Chemometr. – volume: 150 start-page: 77 year: 2005 end-page: 85 article-title: Genetic algorithm applied to the selection of conditions for the simultaneous quantification of three‐food colorants using a hand scanner publication-title: Microchim. Acta – volume: 65 start-page: 67 year: 2003 end-page: 81 article-title: Genetic algorithms and neural networks for quantitative analysis of ternary mixtures using surface plasmon resonance publication-title: Chemometr. Intell. Lab – volume: 58 start-page: 131 year: 2001 end-page: 151 article-title: Some recent developments in PLS mg publication-title: Chemometr. Intell. Lab – year: 1997 – volume: 97 start-page: 9973 year: 1993 end-page: 9976 article-title: Global geometry optimization of clusters using genetic algorithms publication-title: J. Phys. Chem. – volume: 55 start-page: 253 year: 1995 end-page: 259 article-title: A genetic algorithm to search for optimal and suboptimal RNA secondary structures publication-title: Biophys. Chem. – volume: 70 start-page: 193 year: 2004 end-page: 203 article-title: Applications of a genetic algorithm: near optimal estimation of the rate and equilibrium constants of complex reaction mechanism publication-title: Chemometr. Intell. Lab – volume: 97 start-page: 127 year: 2009 end-page: 131 article-title: Analysis of cefalexin with NIR spectrometry coupled to artificial neural networks with modified genetic algorithm for wavelength selection publication-title: Chemometr. Intell. Lab – volume: 45 start-page: 16 year: 2009 end-page: 20 article-title: Fundamentals and applications of genetic algorithms for structure solution from powder X‐ray diffraction data publication-title: Comp. Mat. Sci. – volume: 106 start-page: 10089 year: 2002 end-page: 10095 article-title: An improved genetic algorithm for global optimization and its application to sodium chloride clusters publication-title: J. Phys. Chem. B – volume: 16 start-page: 35 year: 2004 end-page: 41 article-title: Applications of genetic algorithms to computer‐aided drug design publication-title: Prog. Chem. – volume: 10 start-page: 253 year: 1996 end-page: 267 article-title: Network training and architecture optimization by a recursive approach and modified genetic algorithm publication-title: J. Chemometr. – volume: 30 start-page: 619 year: 2006 end-page: 628 article-title: Prediction of acidity constants of thiazolidine‐4‐carbozylic acid derivatives using Ab initio and genetic algorithm‐partial least squares publication-title: Turk. J. Chem. – volume: 101 start-page: 102 year: 2010 end-page: 109 article-title: pKa modeling and prediction of series of pH indicators through genetic algorithm‐least square support vector regression publication-title: Chemometr. Intell. Lab – volume: 27 start-page: 105 year: 2008 end-page: 115 article-title: Genetic algorithm as variable selection procedure for the simulation of 13 C nuclear magnetic resonance spectra of flavonoid derivatives using multiple linear regression publication-title: J. Mol. Graph. Model. – volume: 348 start-page: 409 year: 1997 end-page: 418 article-title: General type of a uniform and reversible representation of chemical structures publication-title: Anal. Chim. Acta – volume: 11 start-page: 433 year: 2003 end-page: 446 article-title: Selection of near infrared wavelengths using genetic algorithms for the determination of seed moisture content publication-title: J. Near Infrared Spec. – volume: 595 start-page: 51 year: 2007 end-page: 58 article-title: Application of genetic algorithm for selection of variables for the BLLS method applied to determination of pesticides and metabolites in wine publication-title: Anal. Chim. Acta – volume: 26 start-page: 29 year: 2007 end-page: 37 article-title: Application of genetic algorithm to determine kinetic parameters of free radical polymerization of vinyl acetate by multi‐objective optimization technique publication-title: Iran. J. Chem. Chem. Eng. – year: 1996 – volume: 20 start-page: 1701 year: 2004 end-page: 1706 article-title: Simultaneous spectrophotometric of p‐benzoquinone and chloranil after microcrystalline naphthalene extraction using genetic algorithm‐based wavelength selection‐partial least squares regression publication-title: Anal. Sci. – volume: 23 start-page: 169 year: 2003 end-page: 196 article-title: Genetic algorithm‐PLS as a tool for wavelength selection in spectral data sets publication-title: Data Handl. Sci. Techn. – volume: 67 start-page: 157 year: 2003 end-page: 166 article-title: Application of uniform design and genetic algorithm in optimization of reversed‐phase chromatographic separation publication-title: Chemometr. Intell. Lab – volume: 66 start-page: 23 year: 1994 end-page: 31 article-title: Curve fitting using natural computation publication-title: Anal. Chem. – volume: 36 start-page: 243 year: 2006 end-page: 255 article-title: Recent developments in multivariate calibration publication-title: Crit. Rev. Anal. Chem. – volume: 76 start-page: 33 year: 2010 end-page: 43 article-title: Modeling and optimization of membrane fabrication using artificial neural network and genetic algirthm publication-title: Sep. Purif. Technol. – volume: 19 start-page: 277 year: 1993 end-page: 293 article-title: Genetic algorithms in chemistry publication-title: Chemometr. Intell. Lab – volume: 1158 start-page: 226 year: 2007 end-page: 233 article-title: Genetic algorithms in chemistry publication-title: J. Chromatogr. A – volume: 75 start-page: 181 year: 2005 end-page: 188 article-title: Application of genetic stochastic resonance algorithm to quantitative structure‐activity relationship study publication-title: Chemometr. Intell. Lab – volume: 261 start-page: 872 year: 1993 end-page: 878 article-title: Genetic algorithms: principles of natural selection applied to computation publication-title: Science – volume: 97 start-page: 69 year: 2007 end-page: 83 article-title: Combination of genetic algorithm and partial least squares for cloud point prediction of nonionic surfactants from molecular structures publication-title: Ann. Chim. – volume: 27 start-page: 955 year: 1999 end-page: 956 article-title: Application of genetic algorithm‐spectrophotometric method for the multicomponent simultaneous determination of rare earth elements in geological samples publication-title: Fenxi Huazue – volume: 690 start-page: 56 year: 2011 end-page: 63 article-title: Prediction of P2Y12 antagonists using a novel genetic algorithm‐support vector machine coupled approach publication-title: Anal. Chim. Acta – volume: 14 start-page: 643 year: 2000 end-page: 655 article-title: Application of genetic algorithm‐PLS for feature selection in spectral data sets publication-title: J. Chemometr. – volume: 158 start-page: B143 year: 2011 end-page: B151 article-title: Optimization design of electrodes for anode‐supported solid oxide fuel cells via genetic algorithm publication-title: J. Electrochem. Soc. – volume: 514 start-page: 211 year: 2004 end-page: 218 article-title: Simultaneous spectrophotometric determination of vitamin K3 and 1,4‐naphthoquinone after cloud point extraction by using genetic algorithm based wavelength selection‐partial least squares regression publication-title: Anal. Chim. Acta – volume: 63 start-page: 15 year: 2002 end-page: 26 article-title: Molecular descriptor selection combining genetic algorithms and fuzzy logic: application to database mining procedure publication-title: Chemometr. Intell. Lab – volume: 23 start-page: 55 year: 2003 end-page: 68 article-title: Hybrid genetic algorithms publication-title: Data Handl. Sci. Techn. – volume: 43 start-page: 1328 year: 2003 end-page: 1334 article-title: Genetic algorithm applied to the selection of factors in principal component‐artificial neural networks: application to QSAR study of calcium channel antagonist activity of 1,4‐dihydropyridines publication-title: J. Chem. Inf. Comp. Sci. – volume: 21 start-page: 609 year: 2001 end-page: 610 article-title: Using genetic algorithm for quantitative analysis of overlapped spectra in FTIR spectra publication-title: Spectroscopy Spectral Anal. – volume: 43 start-page: 157 year: 1998 end-page: 163 article-title: Representative subset selection using genetic algorithms publication-title: Chemometr. Intell. Lab – volume: 261 start-page: 612 year: 1996 end-page: 619 article-title: A genetic algorithm approach to fitting polyatomic spectra via geometry shifts publication-title: Chem. Phys. Lett. – volume: 67 start-page: 4295 year: 1995 end-page: 4301 article-title: Genetic algorithms as a tool for wavelength selection in multivariate calibration publication-title: Anal. Chem. – volume: 38 start-page: 123 year: 1998 end-page: 135 article-title: Application of a genetic algorithm in structure determination from powder diffraction data publication-title: Match – volume: 114 start-page: 358 year: 2009 end-page: 368 article-title: Multiobjective optimization of molded LDPE foams characteristics using genetic algorithm publication-title: J. Appl. Ploym. Sci. – year: 1999 – ident: e_1_2_7_65_1 doi: 10.1016/j.chemolab.2004.07.004 – ident: e_1_2_7_69_1 doi: 10.1016/j.ejmech.2006.12.020 – ident: e_1_2_7_40_1 doi: 10.1021/jp026114 – ident: e_1_2_7_19_1 doi: 10.1016/S0922-3487(03)23010-0 – ident: e_1_2_7_59_1 doi: 10.1016/S0169-7439(02)00068-0 – ident: e_1_2_7_62_1 doi: 10.1016/S0166-1280(02)00619-X – ident: e_1_2_7_68_1 doi: 10.1002/adic.200690087 – volume-title: Handbook of Chemometrics and Qualimetrics, Part A year: 1997 ident: e_1_2_7_5_1 – ident: e_1_2_7_123_1 doi: 10.1016/j.chemolab.2003.11.006 – ident: e_1_2_7_22_1 doi: 10.1002/cem.651 – ident: e_1_2_7_46_1 doi: 10.1016/j.memsci.2010.09.026 – ident: e_1_2_7_55_1 doi: 10.1016/S0169-7439(98)00135-X – ident: e_1_2_7_122_1 doi: 10.1016/S0009-2614(02)01547-6 – ident: e_1_2_7_67_1 doi: 10.1021/ci060087t – ident: e_1_2_7_96_1 doi: 10.1021/ci0255228 – ident: e_1_2_7_39_1 doi: 10.1016/S0003-2670(00)01114-4 – ident: e_1_2_7_16_1 doi: 10.1016/B978-012213810-2/50003-7 – ident: e_1_2_7_17_1 doi: 10.1016/S0922-3487(03)23001-X – ident: e_1_2_7_87_1 doi: 10.1021/ac980451q – ident: e_1_2_7_125_1 doi: 10.1016/j.chemolab.2006.04.004 – ident: e_1_2_7_114_1 doi: 10.1016/j.talanta.2010.07.062 – ident: e_1_2_7_94_1 doi: 10.1016/S0003-2670(01)00910-2 – ident: e_1_2_7_107_1 doi: 10.1002/cem.1000 – ident: e_1_2_7_103_1 doi: 10.2116/analsci.20.1701 – ident: e_1_2_7_26_1 doi: 10.1021/ac00119a015 – ident: e_1_2_7_44_1 doi: 10.1002/app.29609 – ident: e_1_2_7_24_1 doi: 10.1016/j.chroma.2007.04.025 – ident: e_1_2_7_10_1 doi: 10.1016/0169-7439(93)80028-G – ident: e_1_2_7_79_1 doi: 10.1016/0165-9936(91)85132-B – ident: e_1_2_7_106_1 doi: 10.1021/ci049763m – ident: e_1_2_7_80_1 doi: 10.1016/0003-2670(95)00163-T – ident: e_1_2_7_34_1 doi: 10.1002/(SICI)1099-128X(199605)10:3<253::AID-CEM420>3.0.CO;2-Z – ident: e_1_2_7_36_1 doi: 10.1002/(SICI)1096-987X(19970715)18:9<1233::AID-JCC11>3.0.CO;2-6 – volume: 38 start-page: 123 year: 1998 ident: e_1_2_7_120_1 article-title: Application of a genetic algorithm in structure determination from powder diffraction data publication-title: Match – ident: e_1_2_7_95_1 doi: 10.1016/S0003-2670(02)00272-6 – ident: e_1_2_7_110_1 doi: 10.1016/j.aca.2006.12.023 – ident: e_1_2_7_58_1 doi: 10.1016/S0169-7439(02)00033-3 – volume-title: Handbook of Chemometrics and Qualimetrics, Part B year: 1998 ident: e_1_2_7_6_1 – ident: e_1_2_7_86_1 doi: 10.1016/S0169-7439(98)00051-3 – ident: e_1_2_7_20_1 doi: 10.1016/S0922-3487(03)23002-1 – volume-title: An introduction to genetic algorithms year: 1999 ident: e_1_2_7_3_1 – ident: e_1_2_7_12_1 doi: 10.1016/S0165-9936(97)00085-X – volume: 21 start-page: 609 year: 2001 ident: e_1_2_7_92_1 article-title: Using genetic algorithm for quantitative analysis of overlapped spectra in FTIR spectra publication-title: Spectroscopy Spectral Anal. – ident: e_1_2_7_45_1 doi: 10.1016/j.seppur.2010.09.017 – ident: e_1_2_7_93_1 doi: 10.1081/SL-100001446 – ident: e_1_2_7_8_1 doi: 10.1038/376209a0 – ident: e_1_2_7_78_1 doi: 10.1002/cem.1180060506 – ident: e_1_2_7_75_1 doi: 10.1016/j.aca.2011.02.004 – ident: e_1_2_7_76_1 doi: 10.1080/10408340600969924 – volume-title: Review in Computational Chemistry year: 1997 ident: e_1_2_7_29_1 – ident: e_1_2_7_41_1 doi: 10.1016/S0169-7439(03)00091-1 – ident: e_1_2_7_42_1 doi: 10.1556/JPC.18.2005.2.5 – ident: e_1_2_7_49_1 doi: 10.1016/j.desal.2011.01.083 – ident: e_1_2_7_102_1 doi: 10.1016/j.aca.2004.03.048 – ident: e_1_2_7_116_1 doi: 10.1021/ac00073a006 – ident: e_1_2_7_71_1 doi: 10.1365/s10337-008-0608-4 – ident: e_1_2_7_84_1 doi: 10.1016/S0003-2670(97)00065-2 – volume: 31 start-page: 158 year: 2003 ident: e_1_2_7_98_1 article-title: Application of genetic algorithms in resolution of chromatogram publication-title: Fenxi Huaxue – ident: e_1_2_7_101_1 doi: 10.1255/jnirs.394 – ident: e_1_2_7_113_1 doi: 10.1366/000370210791666246 – ident: e_1_2_7_31_1 doi: 10.1016/0169-7439(93)80031-C – ident: e_1_2_7_85_1 doi: 10.1016/S0013-4686(97)00139-4 – ident: e_1_2_7_111_1 doi: 10.1016/j.saa.2008.03.005 – ident: e_1_2_7_51_1 doi: 10.1016/S0003-2670(97)00033-0 – ident: e_1_2_7_100_1 doi: 10.1002/cem.812 – volume: 9 start-page: 651 year: 1998 ident: e_1_2_7_53_1 article-title: Application of genetic algorithm to the QSAR research of pyrrolobenzothiazepinones and pyrrolobenzoxazepinone‐novel and specific non‐nucleoside HIV‐1 reverse transcription inhibitors publication-title: Chin. Chem. Lett. – ident: e_1_2_7_72_1 doi: 10.1016/j.jmgm.2008.03.004 – ident: e_1_2_7_43_1 doi: 10.1016/j.aca.2006.01.048 – volume-title: Adaptation in Natural and Artificial Systems year: 1975 ident: e_1_2_7_2_1 – ident: e_1_2_7_57_1 doi: 10.1021/jm990472s – ident: e_1_2_7_30_1 doi: 10.1016/S0003-2670(99)00081-1 – volume: 50 start-page: 259 year: 2003 ident: e_1_2_7_64_1 article-title: A QSPR study of boiling point of saturated alcohols using genetic algorithm publication-title: Acta Chim. Slov. – volume-title: Chemometrics year: 2007 ident: e_1_2_7_4_1 – ident: e_1_2_7_74_1 doi: 10.2116/analsci.26.897 – ident: e_1_2_7_37_1 doi: 10.1016/S0165-2370(99)00002-9 – ident: e_1_2_7_60_1 doi: 10.1021/ci025661p – ident: e_1_2_7_27_1 doi: 10.1007/BF00124503 – ident: e_1_2_7_112_1 doi: 10.1016/j.chemolab.2009.03.003 – ident: e_1_2_7_9_1 doi: 10.1016/0169-7439(93)80079-W – ident: e_1_2_7_54_1 doi: 10.1016/S0169-7439(98)00148-8 – ident: e_1_2_7_7_1 doi: 10.1126/science.8346439 – volume: 30 start-page: 619 year: 2006 ident: e_1_2_7_66_1 article-title: Prediction of acidity constants of thiazolidine‐4‐carbozylic acid derivatives using Ab initio and genetic algorithm‐partial least squares publication-title: Turk. J. Chem. – ident: e_1_2_7_91_1 doi: 10.1002/1099-128X(200009/12)14:5/6<643::AID-CEM621>3.0.CO;2-E – ident: e_1_2_7_18_1 doi: 10.1016/S0922-3487(03)23012-4 – ident: e_1_2_7_121_1 doi: 10.1021/ci9901284 – ident: e_1_2_7_118_1 doi: 10.1016/0301-4622(94)00130-C – volume: 26 start-page: 29 year: 2007 ident: e_1_2_7_126_1 article-title: Application of genetic algorithm to determine kinetic parameters of free radical polymerization of vinyl acetate by multi‐objective optimization technique publication-title: Iran. J. Chem. Chem. Eng. – ident: e_1_2_7_47_1 doi: 10.1149/1.3517476 – ident: e_1_2_7_50_1 doi: 10.1007/s10910-011-9832-5 – ident: e_1_2_7_81_1 – ident: e_1_2_7_90_1 doi: 10.1366/0003702001951237 – ident: e_1_2_7_104_1 doi: 10.1007/s00604-005-0334-7 – ident: e_1_2_7_23_1 doi: 10.1016/S0922-3487(03)23006-9 – volume: 24 start-page: 37 year: 2005 ident: e_1_2_7_124_1 article-title: Application of genetic algorithm in kinetic modeling and reaction mechanism studies publication-title: Iran. J. Chem. Chem. Eng. – ident: e_1_2_7_56_1 doi: 10.1021/ci990010n – ident: e_1_2_7_32_1 doi: 10.1021/j100141a013 – volume: 27 start-page: 955 year: 1999 ident: e_1_2_7_89_1 article-title: Application of genetic algorithm‐spectrophotometric method for the multicomponent simultaneous determination of rare earth elements in geological samples publication-title: Fenxi Huazue – volume: 16 start-page: 35 year: 2004 ident: e_1_2_7_25_1 article-title: Applications of genetic algorithms to computer‐aided drug design publication-title: Prog. Chem. – ident: e_1_2_7_48_1 doi: 10.1002/app.33252 – ident: e_1_2_7_82_1 doi: 10.1016/S0169-7439(96)00028-7 – ident: e_1_2_7_127_1 doi: 10.1016/j.commatsci.2008.04.032 – ident: e_1_2_7_63_1 doi: 10.1016/S0003-2670(03)00468-9 – ident: e_1_2_7_38_1 doi: 10.1002/(SICI)1096-987X(199903)20:4<455::AID-JCC6>3.0.CO;2-1 – ident: e_1_2_7_88_1 doi: 10.1255/jnirs.192 – ident: e_1_2_7_52_1 doi: 10.1016/j.aca.2004.05.067 – ident: e_1_2_7_108_1 doi: 10.1080/00032710600755868 – ident: e_1_2_7_33_1 doi: 10.1002/anie.199522801 – ident: e_1_2_7_97_1 doi: 10.1016/S0169-7439(02)00104-1 – volume: 40 start-page: 35 year: 2009 ident: e_1_2_7_128_1 article-title: Genetic algorithms and its application to textile publication-title: Textile Asia – ident: e_1_2_7_117_1 doi: 10.1016/S0921-4526(98)00398-6 – ident: e_1_2_7_70_1 doi: 10.1002/qsar.200630159 – ident: e_1_2_7_105_1 doi: 10.1002/elan.200403204 – volume-title: Genetic Algorithms in Molecular Modeling. Principles of QSAR and Drug Design year: 1996 ident: e_1_2_7_28_1 – ident: e_1_2_7_115_1 doi: 10.1002/cem.1339 – ident: e_1_2_7_21_1 doi: 10.1016/S0922-3487(03)23004-5 – ident: e_1_2_7_61_1 doi: 10.1002/cem.891 – ident: e_1_2_7_73_1 doi: 10.1016/j.chemolab.2010.02.003 – ident: e_1_2_7_11_1 doi: 10.1016/0003-2670(94)80155-X – ident: e_1_2_7_14_1 doi: 10.1021/ac9715884 – ident: e_1_2_7_83_1 doi: 10.1016/S0169-7439(96)00062-7 – ident: e_1_2_7_15_1 doi: 10.1016/S0165-9936(98)00011-9 – ident: e_1_2_7_77_1 doi: 10.1016/S0169-7439(01)00156-3 – ident: e_1_2_7_119_1 doi: 10.1016/0009-2614(96)01009-3 – ident: e_1_2_7_13_1 doi: 10.1016/S0169-7439(98)00085-9 – ident: e_1_2_7_99_1 doi: 10.1016/S0039-9140(02)00505-2 – ident: e_1_2_7_35_1 doi: 10.1007/BF00202038 – ident: e_1_2_7_109_1 doi: 10.1134/S1061934807040090 |
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| Title | Genetic algorithms in chemometrics |
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