Ant colony optimisation: a powerful tool for wavelength selection
Ant colony optimisation (ACO) is a meta‐heuristic algorithm, which is derived from the observation of real ants. Real ant colonies are distributed system that, in spite of the simplicity of their individuals, present a highly structured social organisation and can accomplish complex tasks. They alwa...
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| Published in | Journal of chemometrics Vol. 20; no. 3-4; pp. 146 - 157 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Chichester, UK
John Wiley & Sons, Ltd
01.03.2006
Wiley Wiley Subscription Services, Inc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0886-9383 1099-128X 1099-128X |
| DOI | 10.1002/cem.1002 |
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| Abstract | Ant colony optimisation (ACO) is a meta‐heuristic algorithm, which is derived from the observation of real ants. Real ant colonies are distributed system that, in spite of the simplicity of their individuals, present a highly structured social organisation and can accomplish complex tasks. They always find a short path between the nest and a food source. ACO is based on local message exchange via the deposition of pheromone trails. It is in fact a population‐based approach using positive feedback as well as greedy search. Wavelength selection is a strategy used for improving the quality of calibration methods. As a first report, this work indicated that the ACO possesses a great ability to find best subsets of wavelengths, at a short period of time with small PRESS values, via accumulation of information in the form of pheromone trails deposited on each wavelength. Theory of ACO is described and, to carry out the wavelength selection, a fitness function is defined. The ACO parameters are configured with a 3‐levels full factorial design. The high ability of ACO in wavelength selection process was demonstrated by examining four different NIR and UV/Vis data sets via various ACO algorithms, including ACO‐ILS, ACO‐CLS and ACO‐PLS. The results showed that, with the same fitness function, ACO‐ILS algorithm suffers from some overfitting problem. This problem was overcome by constraining the algorithm to choose limited number of wavelengths, the corresponding algorithm called as ACO‐ILS(limited). The results obtained by these algorithms clearly revealed the improved predictive ability of ACO in wavelength selection over the existing full‐spectrum models. Copyright © 2007 John Wiley & Sons, Ltd. |
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| AbstractList | Ant colony optimisation (ACO) is a meta-heuristic algorithm, which is derived from the observation of real ants. Real ant colonies are distributed system that, in spite of the simplicity of their individuals, present a highly structured social organisation and can accomplish complex tasks. They always find a short path between the nest and a food source. ACO is based on local message exchange via the deposition of pheromone trails. It is in fact a population-based approach using positive feedback as well as greedy search. Wavelength selection is a strategy used for improving the quality of calibration methods. As a first report, this work indicated that the ACO possesses a great ability to find best subsets of wavelengths, at a short period of time with small PRESS values, via accumulation of information in the form of pheromone trails deposited on each wavelength. Theory of ACO is described and, to carry out the wavelength selection, a fitness function is defined. The ACO parameters are configured with a 3-levels full factorial design. The high ability of ACO in wavelength selection process was demonstrated by examining four different NIR and UV/Vis data sets via various ACO algorithms, including ACO-ILS, ACO-CLS and ACO-PLS. The results showed that, with the same fitness function, ACO-ILS algorithm suffers from some overfitting problem. This problem was overcome by constraining the algorithm to choose limited number of wavelengths, the corresponding algorithm called as ACO-ILS(limited). The results obtained by these algorithms clearly revealed the improved predictive ability of ACO in wavelength selection over the existing full-spectrum models. Ant colony optimisation (ACO) is a meta‐heuristic algorithm, which is derived from the observation of real ants. Real ant colonies are distributed system that, in spite of the simplicity of their individuals, present a highly structured social organisation and can accomplish complex tasks. They always find a short path between the nest and a food source. ACO is based on local message exchange via the deposition of pheromone trails. It is in fact a population‐based approach using positive feedback as well as greedy search. Wavelength selection is a strategy used for improving the quality of calibration methods. As a first report, this work indicated that the ACO possesses a great ability to find best subsets of wavelengths, at a short period of time with small PRESS values, via accumulation of information in the form of pheromone trails deposited on each wavelength. Theory of ACO is described and, to carry out the wavelength selection, a fitness function is defined. The ACO parameters are configured with a 3‐levels full factorial design. The high ability of ACO in wavelength selection process was demonstrated by examining four different NIR and UV/Vis data sets via various ACO algorithms, including ACO‐ILS, ACO‐CLS and ACO‐PLS. The results showed that, with the same fitness function, ACO‐ILS algorithm suffers from some overfitting problem. This problem was overcome by constraining the algorithm to choose limited number of wavelengths, the corresponding algorithm called as ACO‐ILS(limited). The results obtained by these algorithms clearly revealed the improved predictive ability of ACO in wavelength selection over the existing full‐spectrum models. Copyright © 2007 John Wiley & Sons, Ltd. Ant colony optimisation (ACO) is a meta-heuristic algorithm, which is derived from the observation of real ants. Real ant colonies are distributed system that, in spite of the simplicity of their individuals, present a highly structured social organisation and can accomplish complex tasks. They always find a short path between the nest and a food source. ACO is based on local message exchange via the deposition of pheromone trails. It is in fact a population-based approach using positive feedback as well as greedy search. Wavelength selection is a strategy used for improving the quality of calibration methods. As a first report, this work indicated that the ACO possesses a great ability to find best subsets of wavelengths, at a short period of time with small PRESS values, via accumulation of information in the form of pheromone trails deposited on each wavelength. Theory of ACO is described and, to carry out the wavelength selection, a fitness function is defined. The ACO parameters are configured with a 3-levels full factorial design. The high ability of ACO in wavelength selection process was demonstrated by examining four different NIR and UV/Vis data sets via various ACO algorithms, including ACO-ILS, ACO-CLS and ACO-PLS. The results showed that, with the same fitness function, ACO-ILS algorithm suffers from some overfitting problem. This problem was overcome by constraining the algorithm to choose limited number of wavelengths, the corresponding algorithm called as ACO-ILS(limited). The results obtained by these algorithms clearly revealed the improved predictive ability of ACO in wavelength selection over the existing full-spectrum models. [PUBLICATION ABSTRACT] |
| Author | Hemmateenejad, Bahram Akhond, Morteza Zare-Shahabadi, Vali Shamsipur, Mojtaba |
| Author_xml | – sequence: 1 givenname: Mojtaba surname: Shamsipur fullname: Shamsipur, Mojtaba email: mshamsipur@yahoo.com organization: Department of Chemistry, Razi University, Kermanshah, Iran – sequence: 2 givenname: Vali surname: Zare-Shahabadi fullname: Zare-Shahabadi, Vali organization: Department of Chemistry, Shiraz University, Shiraz, Iran – sequence: 3 givenname: Bahram surname: Hemmateenejad fullname: Hemmateenejad, Bahram organization: Department of Chemistry, Shiraz University, Shiraz, Iran – sequence: 4 givenname: Morteza surname: Akhond fullname: Akhond, Morteza organization: Department of Chemistry, Shiraz University, Shiraz, Iran |
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| Cites_doi | 10.1016/j.talanta.2005.07.045 10.1002/cem.887 10.1002/adic.200590008 10.1080/10629360290014296 10.1021/ac00193a006 10.1021/ac00209a024 10.1016/S0003-2670(00)81909-1 10.1021/ci049610z 10.1021/ac9705733 10.1109/3477.484436 10.7551/mitpress/1290.001.0001 10.1016/S0169-7439(97)00038-5 10.1021/ac011177u 10.1002/1099-128X(200009/12)14:5/6<643::AID-CEM621>3.0.CO;2-E 10.1002/cem.893 10.1109/TEVC.2002.802446 10.1021/ci0255228 10.1016/S0169-7439(96)00062-7 10.1016/j.talanta.2005.03.025 10.1016/0924-2031(90)80005-O 10.1016/S0003-2670(99)00375-X 10.1287/ijoc.12.3.237.12636 10.1016/0003-2670(94)80155-X 10.1002/0470863242 10.1016/j.aca.2004.03.048 10.1016/S0169-7439(01)00119-8 |
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| Keywords | wavelength selection Selection multivariate calibration Calibration Algorithm ant colony optimisation Chemometrics Wavelength |
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| References | Araujo MCU, Saldanha TCB, Galvao RKH, Oneyama T, Chame HC, Visani V. The successive projections algorithm for variable selection in spectroscopic multicomponent analysis. Chemometr. Intell. Lab. Syst. 2001; 57: 65-73. Lucasius CB, Beckers MLM, Kateman G. Genetic algorithms in wavelength selection: a comparative study. Anal. Chim. Acta. 1994; 286: 135-153. Ding P, Su QD, Wu QS. Ant colony algorithm in chemistry and its application in first derivative fluorescent spectra analyzing. Chem. J. Chinese Univ. 2002; 23: 1695-1697. Izrailev S, Agrafiotis DK. Variable selection for QSAR by artificial ant colony systems. SAR & QSAR Environment. Res. 2002; 13: 417-423. Liang YZ, Xie YL, Yu RQ. Accuracy criteria and optimal wavelength selection for multicomponent spectrophotometric determinations. Anal. Chim. Acta. 1989; 222: 347-357. Mevik BH. Cedekvist. Mean squared error of prediction (MSEP) estimates for principle component regression (PCR) and partial least squares regression (PLSR). J. Chemometri. 2004; 18: 422-429. Leardi R, N¢rgaard L. Sequential application of backward interval partial least squares and genetic algorithms for the selection of relevant spectral regions. J. Chemometri. 2004; 18: 486-497. Shen Q, Jiang JH, Tao JC, Shen G, Yu RQ. Modified ant colony optimization algorithm for variable selection in QSAR modeling: QSAR studies of cyclooxygenase inhibitors. J. Chem. Inf. Model. 2005; 45: 1024-1029. Azubel M, Fernández FM, Tudino MB, Troccoli OE. Novel application and comparison of multivariate calibration for the simultaneous determination of Cu, Zn and Mn at trace levels using flow injection diode array spectrophotometry. Anal. Chim. Acta. 1999; 398: 93-102. Dorigo M, Gambardella ML, Middendorf M, Stutzle T. Especial section on "Ant Colony Optimization". IEEE Trans. Evolut. Comput. 2002; 6: 317-365. Thomas EV, Haaland DM. Comparison of multivariate calibration methods for quantitative spectral analysis. Anal. Chem. 1990; 62: 1091-1099. Leardi R. Application of genetic algorithm-PLS for feature selection in spectral data sets. J. Chemomert. 2000; 14: 643-655. Rimbaud DR, Massart DL, de Noord OE. Random correlation in variable selection for multivariate calibration with a genetic algorithm. Chemom. Intell. Lab. Sys. 1996; 35: 213-220. Goicoechea HC, Olivieri AC. Wavelength selection for multivariate calibration using a genetic algorithm: a novel initialization strategy. J. Chem. Inf. Comput. Sci. 2002; 42: 1146-1153. Dorigo M, Stutzle T. Ant Colony Optimization. MIT Press: New York, 2004. Spiegelman CH, McShane MJ, Goetz MJ, Motamedi M, Yue QL, Cote GL. Theoretical justification of wavelength selection in PLS calibration: development of a new algorithm. Anal. Chem. 1998; 70: 35-44. Galvão RKH, Araujo MCU, José GE, Pontes MJC, Silva EC, Saldanha TCB. A method for calibration and validation subset partitioning. Talanta. 2005; 67: 736-740. Kalivas JH, Roberts N, Sutter MJ. Global optimization by simulated annealing with wavelength selection for ultraviolet-visible spectrophotometry. Anal. Chem. 1989; 61: 2024-2030. Dorigo M, Maniezzo V, Colorni A. Ant system: optimization by a colony of cooperating agents. IEEE Trans. Sys. Man Cybernetics, Part B. 1996; 26: 29-41. Gambardella LM, Dorigo M. Ant Colony System hybridized with a new local search for the sequential ordering problem. INFORMS J. Comput. 2000; 12: 237- 255. Dorigo M, Caro GD. Ant colony optimization: a new meta-heuristic. IEEE. 1999; 1470-1477. Shamsipur M, Ghavami H, Hemmateenejad B, Sharghi H. Anal. di Chim. 2005; 95: 63. Haaland DM, Higgins KL, Tallant DR. Multivariate calibration of carbon Raman spectra for quantitative determination of peak temperature history. Vib. Spec. 1990; 1: 35-40. Martens H, Naes T. Multivariate Calibration. Wiley & Sons: New York, 1989. Jiang JH, Berry RJ, Siesler HW, Ozaki Y. Wavelength interval selection in multicomponent spectral analysis by moving window partial least-squares regression with applications to mid-infrared and near-infrared spectroscopic data. Anal. Chem. 2002; 74: 3555-3565. 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. Hemmateenjad B, Ghavami R, Miri R, Shamsipur M. Net analyte signal-based simultaneous determination of antazoline and naphazoline using wavelength region selection by experimental design-neural networks. Talanta 2006; 68: 1222-1229. Brereton RG. Chemometrics: Data Analysis for the Laboratory and Chemical Plant. John Wiley & Sons: New York, 2003. Corne D, Dorigo M, Glover F. New Ideas in Optimization. McGraw-Hill International: London, 1999. Kalivas JH. Two data sets of near infrared spectra. Chemometr. Intell. Lab. Syst. 1997; 37: 255. 1989; 61 2002; 74 2002; 6 2002; 13 2004 1992 2003 1991 1996; 35 2005; 45 2005; 67 1999 1990; 62 1990; 1 1994; 286 1989; 222 2000; 14 2004; 18 2006; 68 2002; 42 2000; 12 2002; 23 1997; 37 2005; 95 1998; 70 1999; 398 2004; 514 2001; 57 1996; 26 1989 Corne D (e_1_2_1_26_2) 1999 Martens H (e_1_2_1_3_2) 1989 e_1_2_1_22_2 e_1_2_1_23_2 e_1_2_1_20_2 e_1_2_1_21_2 e_1_2_1_27_2 e_1_2_1_25_2 e_1_2_1_28_2 Dorigo M (e_1_2_1_29_2) 1999 Ding P (e_1_2_1_24_2) 2002; 23 e_1_2_1_6_2 e_1_2_1_30_2 e_1_2_1_7_2 e_1_2_1_4_2 e_1_2_1_5_2 e_1_2_1_2_2 e_1_2_1_11_2 e_1_2_1_34_2 e_1_2_1_12_2 e_1_2_1_33_2 e_1_2_1_32_2 e_1_2_1_10_2 e_1_2_1_31_2 e_1_2_1_15_2 e_1_2_1_16_2 e_1_2_1_13_2 e_1_2_1_14_2 e_1_2_1_19_2 e_1_2_1_8_2 e_1_2_1_17_2 e_1_2_1_9_2 e_1_2_1_18_2 |
| References_xml | – reference: Thomas EV, Haaland DM. Comparison of multivariate calibration methods for quantitative spectral analysis. Anal. Chem. 1990; 62: 1091-1099. – reference: Ding P, Su QD, Wu QS. Ant colony algorithm in chemistry and its application in first derivative fluorescent spectra analyzing. Chem. J. Chinese Univ. 2002; 23: 1695-1697. – reference: Araujo MCU, Saldanha TCB, Galvao RKH, Oneyama T, Chame HC, Visani V. The successive projections algorithm for variable selection in spectroscopic multicomponent analysis. Chemometr. Intell. Lab. Syst. 2001; 57: 65-73. – reference: Martens H, Naes T. Multivariate Calibration. Wiley & Sons: New York, 1989. – reference: Dorigo M, Stutzle T. Ant Colony Optimization. MIT Press: New York, 2004. – reference: Azubel M, Fernández FM, Tudino MB, Troccoli OE. Novel application and comparison of multivariate calibration for the simultaneous determination of Cu, Zn and Mn at trace levels using flow injection diode array spectrophotometry. Anal. Chim. Acta. 1999; 398: 93-102. – reference: Leardi R, N¢rgaard L. Sequential application of backward interval partial least squares and genetic algorithms for the selection of relevant spectral regions. J. Chemometri. 2004; 18: 486-497. – reference: Kalivas JH. Two data sets of near infrared spectra. Chemometr. Intell. Lab. Syst. 1997; 37: 255. – reference: Dorigo M, Maniezzo V, Colorni A. Ant system: optimization by a colony of cooperating agents. IEEE Trans. Sys. Man Cybernetics, Part B. 1996; 26: 29-41. – reference: Dorigo M, Caro GD. Ant colony optimization: a new meta-heuristic. IEEE. 1999; 1470-1477. – reference: Liang YZ, Xie YL, Yu RQ. Accuracy criteria and optimal wavelength selection for multicomponent spectrophotometric determinations. Anal. Chim. Acta. 1989; 222: 347-357. – reference: Gambardella LM, Dorigo M. Ant Colony System hybridized with a new local search for the sequential ordering problem. INFORMS J. Comput. 2000; 12: 237- 255. – 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: Izrailev S, Agrafiotis DK. Variable selection for QSAR by artificial ant colony systems. SAR & QSAR Environment. Res. 2002; 13: 417-423. – reference: Lucasius CB, Beckers MLM, Kateman G. Genetic algorithms in wavelength selection: a comparative study. Anal. Chim. Acta. 1994; 286: 135-153. – reference: Corne D, Dorigo M, Glover F. New Ideas in Optimization. McGraw-Hill International: London, 1999. – reference: Haaland DM, Higgins KL, Tallant DR. Multivariate calibration of carbon Raman spectra for quantitative determination of peak temperature history. Vib. Spec. 1990; 1: 35-40. – reference: Mevik BH. Cedekvist. Mean squared error of prediction (MSEP) estimates for principle component regression (PCR) and partial least squares regression (PLSR). J. Chemometri. 2004; 18: 422-429. – reference: Shamsipur M, Ghavami H, Hemmateenejad B, Sharghi H. Anal. di Chim. 2005; 95: 63. – reference: Hemmateenjad B, Ghavami R, Miri R, Shamsipur M. Net analyte signal-based simultaneous determination of antazoline and naphazoline using wavelength region selection by experimental design-neural networks. Talanta 2006; 68: 1222-1229. – reference: Shen Q, Jiang JH, Tao JC, Shen G, Yu RQ. Modified ant colony optimization algorithm for variable selection in QSAR modeling: QSAR studies of cyclooxygenase inhibitors. J. Chem. Inf. Model. 2005; 45: 1024-1029. – reference: Rimbaud DR, Massart DL, de Noord OE. Random correlation in variable selection for multivariate calibration with a genetic algorithm. Chemom. Intell. Lab. Sys. 1996; 35: 213-220. – reference: Dorigo M, Gambardella ML, Middendorf M, Stutzle T. Especial section on "Ant Colony Optimization". IEEE Trans. Evolut. Comput. 2002; 6: 317-365. – reference: Galvão RKH, Araujo MCU, José GE, Pontes MJC, Silva EC, Saldanha TCB. A method for calibration and validation subset partitioning. Talanta. 2005; 67: 736-740. – reference: Kalivas JH, Roberts N, Sutter MJ. Global optimization by simulated annealing with wavelength selection for ultraviolet-visible spectrophotometry. Anal. Chem. 1989; 61: 2024-2030. – reference: Jiang JH, Berry RJ, Siesler HW, Ozaki Y. Wavelength interval selection in multicomponent spectral analysis by moving window partial least-squares regression with applications to mid-infrared and near-infrared spectroscopic data. Anal. Chem. 2002; 74: 3555-3565. – reference: Brereton RG. Chemometrics: Data Analysis for the Laboratory and Chemical Plant. John Wiley & Sons: New York, 2003. – reference: Spiegelman CH, McShane MJ, Goetz MJ, Motamedi M, Yue QL, Cote GL. Theoretical justification of wavelength selection in PLS calibration: development of a new algorithm. Anal. Chem. 1998; 70: 35-44. – reference: Goicoechea HC, Olivieri AC. Wavelength selection for multivariate calibration using a genetic algorithm: a novel initialization strategy. J. Chem. Inf. Comput. Sci. 2002; 42: 1146-1153. – reference: Leardi R. Application of genetic algorithm-PLS for feature selection in spectral data sets. J. Chemomert. 2000; 14: 643-655. – 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. Chemomert. – volume: 26 start-page: 29 year: 1996 end-page: 41 article-title: Ant system: optimization by a colony of cooperating agents publication-title: IEEE Trans. Sys. Man Cybernetics, Part B. – start-page: 134 year: 1991 end-page: 142 – volume: 95 start-page: 63 year: 2005 publication-title: Anal. di Chim. – volume: 398 start-page: 93 year: 1999 end-page: 102 article-title: Novel application and comparison of multivariate calibration for the simultaneous determination of Cu, Zn and Mn at trace levels using flow injection diode array spectrophotometry publication-title: Anal. Chim. Acta. – volume: 18 start-page: 422 year: 2004 end-page: 429 article-title: Cedekvist. Mean squared error of prediction (MSEP) estimates for principle component regression (PCR) and partial least squares regression (PLSR) publication-title: J. Chemometri. – year: 1989 – year: 2003 – 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: 6 start-page: 317 year: 2002 end-page: 365 article-title: Especial section on “Ant Colony Optimization” publication-title: IEEE Trans. Evolut. Comput. – volume: 222 start-page: 347 year: 1989 end-page: 357 article-title: Accuracy criteria and optimal wavelength selection for multicomponent spectrophotometric determinations publication-title: Anal. Chim. Acta. – start-page: 1470 year: 1999 end-page: 1477 article-title: Ant colony optimization: a new meta‐heuristic publication-title: IEEE. – volume: 18 start-page: 486 year: 2004 end-page: 497 article-title: Sequential application of backward interval partial least squares and genetic algorithms for the selection of relevant spectral regions publication-title: J. Chemometri. – year: 1992 – volume: 42 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. Comput. Sci. – volume: 61 start-page: 2024 year: 1989 end-page: 2030 article-title: Global optimization by simulated annealing with wavelength selection for ultraviolet‐visible spectrophotometry publication-title: Anal. Chem. – volume: 62 start-page: 1091 year: 1990 end-page: 1099 article-title: Comparison of multivariate calibration methods for quantitative spectral analysis publication-title: Anal. Chem. – volume: 74 start-page: 3555 year: 2002 end-page: 3565 article-title: Wavelength interval selection in multicomponent spectral analysis by moving window partial least‐squares regression with applications to mid‐infrared and near‐infrared spectroscopic data publication-title: Anal. Chem. – 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: Chemom. Intell. Lab. Sys. – volume: 67 start-page: 736 year: 2005 end-page: 740 article-title: A method for calibration and validation subset partitioning publication-title: Talanta. – volume: 23 start-page: 1695 year: 2002 end-page: 1697 article-title: Ant colony algorithm in chemistry and its application in first derivative fluorescent spectra analyzing publication-title: Chem. J. Chinese Univ. – volume: 68 start-page: 1222 year: 2006 end-page: 1229 article-title: Net analyte signal‐based simultaneous determination of antazoline and naphazoline using wavelength region selection by experimental design‐neural networks publication-title: Talanta – volume: 13 start-page: 417 year: 2002 end-page: 423 article-title: Variable selection for QSAR by artificial ant colony systems publication-title: SAR & QSAR Environment. Res. – volume: 12 start-page: 237 year: 2000 end-page: 255 article-title: Ant Colony System hybridized with a new local search for the sequential ordering problem publication-title: INFORMS J. Comput. – year: 2004 – volume: 57 start-page: 65 year: 2001 end-page: 73 article-title: The successive projections algorithm for variable selection in spectroscopic multicomponent analysis publication-title: Chemometr. Intell. Lab. Syst. – volume: 1 start-page: 35 year: 1990 end-page: 40 article-title: Multivariate calibration of carbon Raman spectra for quantitative determination of peak temperature history publication-title: Vib. Spec. – volume: 70 start-page: 35 year: 1998 end-page: 44 article-title: Theoretical justification of wavelength selection in PLS calibration: development of a new algorithm publication-title: Anal. Chem. – volume: 45 start-page: 1024 year: 2005 end-page: 1029 article-title: Modified ant colony optimization algorithm for variable selection in QSAR modeling: QSAR studies of cyclooxygenase inhibitors publication-title: J. Chem. Inf. Model. – volume: 514 start-page: 211 year: 2004 end-page: 218 article-title: Simultaneous spectrophotometric determination of Vitamin K 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: 37 start-page: 255 year: 1997 article-title: Two data sets of near infrared spectra publication-title: Chemometr. Intell. Lab. Syst. – year: 1999 – ident: e_1_2_1_15_2 doi: 10.1016/j.talanta.2005.07.045 – ident: e_1_2_1_28_2 doi: 10.1002/cem.887 – ident: e_1_2_1_31_2 doi: 10.1002/adic.200590008 – ident: e_1_2_1_22_2 doi: 10.1080/10629360290014296 – volume-title: Multivariate Calibration year: 1989 ident: e_1_2_1_3_2 – ident: e_1_2_1_10_2 doi: 10.1021/ac00193a006 – ident: e_1_2_1_5_2 doi: 10.1021/ac00209a024 – ident: e_1_2_1_11_2 doi: 10.1016/S0003-2670(00)81909-1 – ident: e_1_2_1_23_2 doi: 10.1021/ci049610z – ident: e_1_2_1_7_2 doi: 10.1021/ac9705733 – ident: e_1_2_1_25_2 doi: 10.1109/3477.484436 – ident: e_1_2_1_27_2 doi: 10.7551/mitpress/1290.001.0001 – ident: e_1_2_1_32_2 doi: 10.1016/S0169-7439(97)00038-5 – ident: e_1_2_1_14_2 doi: 10.1021/ac011177u – ident: e_1_2_1_12_2 doi: 10.1002/1099-128X(200009/12)14:5/6<643::AID-CEM621>3.0.CO;2-E – ident: e_1_2_1_16_2 doi: 10.1002/cem.893 – ident: e_1_2_1_33_2 – ident: e_1_2_1_20_2 doi: 10.1109/TEVC.2002.802446 – ident: e_1_2_1_17_2 doi: 10.1021/ci0255228 – volume: 23 start-page: 1695 year: 2002 ident: e_1_2_1_24_2 article-title: Ant colony algorithm in chemistry and its application in first derivative fluorescent spectra analyzing publication-title: Chem. J. Chinese Univ. – ident: e_1_2_1_8_2 doi: 10.1016/S0169-7439(96)00062-7 – ident: e_1_2_1_34_2 doi: 10.1016/j.talanta.2005.03.025 – ident: e_1_2_1_2_2 doi: 10.1016/0924-2031(90)80005-O – volume-title: New Ideas in Optimization year: 1999 ident: e_1_2_1_26_2 – ident: e_1_2_1_19_2 – ident: e_1_2_1_4_2 doi: 10.1016/S0003-2670(99)00375-X – ident: e_1_2_1_21_2 doi: 10.1287/ijoc.12.3.237.12636 – ident: e_1_2_1_9_2 doi: 10.1016/0003-2670(94)80155-X – ident: e_1_2_1_30_2 doi: 10.1002/0470863242 – ident: e_1_2_1_18_2 – start-page: 1470 year: 1999 ident: e_1_2_1_29_2 article-title: Ant colony optimization: a new meta‐heuristic publication-title: IEEE. – ident: e_1_2_1_6_2 doi: 10.1016/j.aca.2004.03.048 – ident: e_1_2_1_13_2 doi: 10.1016/S0169-7439(01)00119-8 |
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| SubjectTerms | Algorithms ant colony optimisation Calibration Chemistry Exact sciences and technology General and physical chemistry multivariate calibration Parameter optimization Theory wavelength selection Wavelengths |
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| Title | Ant colony optimisation: a powerful tool for wavelength selection |
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