ABSTRACT
Extreme weather is frequent and aggressive, posing a huge challenge to urban management capacity. The construction of urban resilience is a systematic project of multi-system coordination. Previous studies have focused on temporal evolution, external system coupling and coordination, and less on the internal study of urban resilience systems. Based on the perspective of the Wuli-Shili-Renli methodology, the study combines urban resilience with Eastern management philosophy. Using a coupled coordination model, the evolutionary laws of key elements of multiple processes in the complex urban resilience system of Henan Province are studied. The coupled coordination mechanism of multiple elements and processes in the province is revealed. It is found that (1) the development of the urban resilient system in Henan Province has gone through two stages from fluctuation to stability. From 2010 to 2015 called "fluctuating growth" and from 2016 to 2019 called "linear growth". (2) There are three different periods of development for the coordination of the urban resilient system in Henan. Stage 1 (2010-2015) the "coupling teething period", stage 2 (2016-2017) the "decoupling accumulation period" and stage 3 (2018-2019) the "self-organized explosive period". (3) Henan has strong preventive power, but weak resistance and recovery power. Then, from the perspective of WSR, the optimal regulation of the regional urban resilient system is proposed.
ABSTRACT
With the rapid development of tourism, professional tourism villages emerge one after another, which has become the focus of the tourism industry. At present, there are some problems in tourism professional villages, such as imperfect management and inaccurate prediction of future development, which affect the rational allocation of tourism resources. In order to improve the distribution of tourism resources and better predict the development of tourism professional villages, it is necessary to make comprehensive judgment and analysis, especially the analysis of indicators such as the prediction and development judgment of tourism professional villages. This paper discusses the optimization analysis of the agglomeration of tourism specialized villages by backpropagation (BP) neural network and system dynamics model, analyzes the system structure of the agglomeration factors of tourism specialized villages, and promotes the intelligent integration of the agglomeration factors. The development of clusters of professional villages promotes data integration among resources, economy, society, and other elements and presents the characteristics of big data. As the level of concentration of professional villages increases, the complexity of the associated factors also increases, which increases the difficulty and effectiveness of tourism analysis. In view of this situation, taking mountain tourism as the research object, this paper proposes an improved system dynamics model based on BP, extracts features from cross factor (resource, economic, and social) data, and optimizes the relationship between professional village agglomeration and various factors. The MATLAB simulation results show that based on the improved system dynamics analysis, the simplification rate of (resources, economy, and society) data can be controlled at more than 24%, the degree of agglomeration is more than 95%, and the construction time of the relationship map of related factors is less than 40 s. Therefore, the analysis method proposed in this paper is suitable for the calculation of the agglomeration of tourism professional villages in the mountain area and can meet the needs of the development of tourism professional villages in the mountain area.
