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.

The new development pattern of "dual circulation" raises interesting questions regarding new pathways of coordinated development between the tourism industry and urbanization. The Guangdong-Hong Kong-Macao Greater Bay Area (Greater Bay Area) is a connecting area of internal and external circulation of China’s economy, and accordingly, this paper selects the “9 + 2” urban agglomeration of the Greater Bay Area as the study area. Given the differences in statistical indexes and units among Guangdong, Hong Kong and Macao, this paper selects suitable indexes to establish an evaluation system for development of the tourism industry and new-type urbanization. The paper then calculates the comprehensive development level and coupling coordination degree of the tourism industry and new-type urbanization in the 11 cities of the Greater Bay Area from 2010 to 2019 using the entropy method and coupling coordination degree model. The results show that the comprehensive development levels of and coupling coordination degree between the tourism industry and new-type urbanization in the 11 cities exhibit evident grading. Ranking the high-quality development level from high to low, the 11 cities can be divided into three echelons: Guangzhou is the first echelon, Shenzhen and Hong Kong are the second echelon, and the other cities are the third echelon. All 11 cities exhibited a steady development trend in the period. Accordingly, this paper further puts forward countermeasures and suggestions to cope with the "dual circulation" strategy and continuously enhance the benign interaction between the development of the tourism industry and the process of urbanization.