Comprehensive Evaluation of Tourism Resources Based on Multispecies Evolutionary Genetic Algorithm-Enabled Neural Networks

Author:

Kan Xinglong1ORCID,Li Lin2

Affiliation:

1. Tourism School, Zhuhai College of Science and Technology, Zhuhai 519000, China

2. Overseas Chinese Town Holdings Company, Ltd, Shenzhen 518034, China

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.

Funder

Department of Education of Guangdong Province

Publisher

Hindawi Limited

Subject

General Mathematics,General Medicine,General Neuroscience,General Computer Science

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