Cargando…
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 b...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8691991/ https://www.ncbi.nlm.nih.gov/pubmed/34950196 http://dx.doi.org/10.1155/2021/1081814 |
_version_ | 1784618864964796416 |
---|---|
author | Kan, Xinglong Li, Lin |
author_facet | Kan, Xinglong Li, Lin |
author_sort | Kan, Xinglong |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8691991 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-86919912021-12-22 Comprehensive Evaluation of Tourism Resources Based on Multispecies Evolutionary Genetic Algorithm-Enabled Neural Networks Kan, Xinglong Li, Lin Comput Intell Neurosci Research Article 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. Hindawi 2021-12-14 /pmc/articles/PMC8691991/ /pubmed/34950196 http://dx.doi.org/10.1155/2021/1081814 Text en Copyright © 2021 Xinglong Kan and Lin Li. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Kan, Xinglong Li, Lin Comprehensive Evaluation of Tourism Resources Based on Multispecies Evolutionary Genetic Algorithm-Enabled Neural Networks |
title | Comprehensive Evaluation of Tourism Resources Based on Multispecies Evolutionary Genetic Algorithm-Enabled Neural Networks |
title_full | Comprehensive Evaluation of Tourism Resources Based on Multispecies Evolutionary Genetic Algorithm-Enabled Neural Networks |
title_fullStr | Comprehensive Evaluation of Tourism Resources Based on Multispecies Evolutionary Genetic Algorithm-Enabled Neural Networks |
title_full_unstemmed | Comprehensive Evaluation of Tourism Resources Based on Multispecies Evolutionary Genetic Algorithm-Enabled Neural Networks |
title_short | Comprehensive Evaluation of Tourism Resources Based on Multispecies Evolutionary Genetic Algorithm-Enabled Neural Networks |
title_sort | comprehensive evaluation of tourism resources based on multispecies evolutionary genetic algorithm-enabled neural networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8691991/ https://www.ncbi.nlm.nih.gov/pubmed/34950196 http://dx.doi.org/10.1155/2021/1081814 |
work_keys_str_mv | AT kanxinglong comprehensiveevaluationoftourismresourcesbasedonmultispeciesevolutionarygeneticalgorithmenabledneuralnetworks AT lilin comprehensiveevaluationoftourismresourcesbasedonmultispeciesevolutionarygeneticalgorithmenabledneuralnetworks |