Comprehensive Evaluation of Tourism Resources Based on Multispecies Evolutionary Genetic Algorithm-Enabled Neural Networks
With the development of neural network technology and the rapid growth of China’s tourism economic income at this stage, the research on the comprehensive evaluation of tourism resources has gradually emerged. Based on this, this paper studies the neural network comprehensive evaluation model based...
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| Published in | Computational intelligence and neuroscience Vol. 2021; no. 1; p. 1081814 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Hindawi
2021
John Wiley & Sons, Inc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1687-5265 1687-5273 1687-5273 |
| DOI | 10.1155/2021/1081814 |
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| Abstract | With the development of neural network technology and the rapid growth of China’s tourism economic income at this stage, the research on the comprehensive evaluation of tourism resources has gradually emerged. Based on this, this paper studies the neural network comprehensive evaluation model based on multispecies evolutionary genetic algorithm and designs the neural network analysis system of influencing factors of tourism resources based on multispecies evolutionary genetic algorithm. The collection and acquisition of data information are realized from the aspects of resource income status, tourism development investment, and sustainability evaluation in the tourism area. The multispecies evolutionary genetic algorithm is used for comprehensive analysis and evaluation. The algorithm can realize the complex analysis and comprehensive evaluation of the core influencing factors of neural network. Accurate analysis and evaluation were carried out according to the different characteristics of tourism resources and the current situation of tourism income. The results show that the neural network comprehensive evaluation model based on multispecies evolutionary genetic algorithm has the advantages of high practicability, good sorting effect of variable ratio, and good data integration. It can effectively analyze and compare the comprehensive evaluation factors affecting tourism resources in different ratios. |
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| AbstractList | With the development of neural network technology and the rapid growth of China’s tourism economic income at this stage, the research on the comprehensive evaluation of tourism resources has gradually emerged. Based on this, this paper studies the neural network comprehensive evaluation model based on multispecies evolutionary genetic algorithm and designs the neural network analysis system of influencing factors of tourism resources based on multispecies evolutionary genetic algorithm. The collection and acquisition of data information are realized from the aspects of resource income status, tourism development investment, and sustainability evaluation in the tourism area. The multispecies evolutionary genetic algorithm is used for comprehensive analysis and evaluation. The algorithm can realize the complex analysis and comprehensive evaluation of the core influencing factors of neural network. Accurate analysis and evaluation were carried out according to the different characteristics of tourism resources and the current situation of tourism income. The results show that the neural network comprehensive evaluation model based on multispecies evolutionary genetic algorithm has the advantages of high practicability, good sorting effect of variable ratio, and good data integration. It can effectively analyze and compare the comprehensive evaluation factors affecting tourism resources in different ratios. With the development of neural network technology and the rapid growth of China's tourism economic income at this stage, the research on the comprehensive evaluation of tourism resources has gradually emerged. Based on this, this paper studies the neural network comprehensive evaluation model based on multispecies evolutionary genetic algorithm and designs the neural network analysis system of influencing factors of tourism resources based on multispecies evolutionary genetic algorithm. The collection and acquisition of data information are realized from the aspects of resource income status, tourism development investment, and sustainability evaluation in the tourism area. The multispecies evolutionary genetic algorithm is used for comprehensive analysis and evaluation. The algorithm can realize the complex analysis and comprehensive evaluation of the core influencing factors of neural network. Accurate analysis and evaluation were carried out according to the different characteristics of tourism resources and the current situation of tourism income. The results show that the neural network comprehensive evaluation model based on multispecies evolutionary genetic algorithm has the advantages of high practicability, good sorting effect of variable ratio, and good data integration. It can effectively analyze and compare the comprehensive evaluation factors affecting tourism resources in different ratios.With the development of neural network technology and the rapid growth of China's tourism economic income at this stage, the research on the comprehensive evaluation of tourism resources has gradually emerged. Based on this, this paper studies the neural network comprehensive evaluation model based on multispecies evolutionary genetic algorithm and designs the neural network analysis system of influencing factors of tourism resources based on multispecies evolutionary genetic algorithm. The collection and acquisition of data information are realized from the aspects of resource income status, tourism development investment, and sustainability evaluation in the tourism area. The multispecies evolutionary genetic algorithm is used for comprehensive analysis and evaluation. The algorithm can realize the complex analysis and comprehensive evaluation of the core influencing factors of neural network. Accurate analysis and evaluation were carried out according to the different characteristics of tourism resources and the current situation of tourism income. The results show that the neural network comprehensive evaluation model based on multispecies evolutionary genetic algorithm has the advantages of high practicability, good sorting effect of variable ratio, and good data integration. It can effectively analyze and compare the comprehensive evaluation factors affecting tourism resources in different ratios. |
| Audience | Academic |
| Author | Li, Lin Kan, Xinglong |
| AuthorAffiliation | 1 Tourism School, Zhuhai College of Science and Technology, Zhuhai 519000, China 2 Overseas Chinese Town Holdings Company, Ltd, Shenzhen 518034, China |
| AuthorAffiliation_xml | – name: 2 Overseas Chinese Town Holdings Company, Ltd, Shenzhen 518034, China – name: 1 Tourism School, Zhuhai College of Science and Technology, Zhuhai 519000, China |
| Author_xml | – sequence: 1 givenname: Xinglong orcidid: 0000-0001-6445-0439 surname: Kan fullname: Kan, Xinglong organization: Tourism SchoolZhuhai College of Science and TechnologyZhuhai 519000China – sequence: 2 givenname: Lin surname: Li fullname: Li, Lin organization: Overseas Chinese Town Holdings Company, LtdShenzhen 518034China |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34950196$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1155_2023_9842926 crossref_primary_10_1155_2022_5422210 crossref_primary_10_1155_2022_7196163 crossref_primary_10_21511_ppm_20_4__2022_43 |
| Cites_doi | 10.1016/j.ijheatmasstransfer.2020.119952 10.1111/j.1461-0248.2008.01153.x 10.1016/j.energy.2020.117841 10.1109/4235.996017 10.17721/2308-135x.2019.53.69-76 10.1109/JIOT.2020.2993030 10.1002/cjoc.201190204 10.1504/ijcc.2020.10034633 10.1016/j.cnsns.2021.105833 10.1007/s11192-019-03050-x 10.1016/j.yofte.2020.102229 10.1016/j.asoc.2020.106078 10.1016/j.ijleo.2021.166273 10.1007/s11069-020-04089-3 10.1108/IJIUS-02-2019-0011 10.1088/1742-6596/1629/1/012072 10.1007/s00158-020-02766-2 10.5373/jardcs/v12i5/20201712 10.2514/3.11868 10.1088/1757-899x/1123/1/012011 10.1016/j.scs.2020.102391 10.1016/j.engappai.2020.103905 10.1088/1742-6596/1833/1/012062 10.1007/s10706-018-0549-0 10.1016/j.eswa.2020.113232 10.1614/WS-06-083.1 10.1007/s10586-021-03254-y |
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| Copyright | Copyright © 2021 Xinglong Kan and Lin Li. COPYRIGHT 2021 John Wiley & Sons, Inc. Copyright © 2021 Xinglong Kan and Lin Li. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 Copyright © 2021 Xinglong Kan and Lin Li. 2021 |
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| Snippet | With the development of neural network technology and the rapid growth of China’s tourism economic income at this stage, the research on the comprehensive... With the development of neural network technology and the rapid growth of China's tourism economic income at this stage, the research on the comprehensive... |
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| SubjectTerms | Algorithms Analysis Biological Evolution China Data integration Evolution Evolutionary algorithms Experiments Genetic algorithms Genetic analysis Genetic research Income Network analysis Neural networks Neural Networks, Computer Optimization Regions Simulation Sorting algorithms Sustainability Sustainable development Technology Tourism Travel industry |
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| Title | Comprehensive Evaluation of Tourism Resources Based on Multispecies Evolutionary Genetic Algorithm-Enabled Neural Networks |
| URI | https://dx.doi.org/10.1155/2021/1081814 https://www.ncbi.nlm.nih.gov/pubmed/34950196 https://www.proquest.com/docview/2613962275 https://www.proquest.com/docview/2614230480 https://pubmed.ncbi.nlm.nih.gov/PMC8691991 https://downloads.hindawi.com/journals/cin/2021/1081814.pdf |
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