Analysis and Research on Sustainable Development Factors of the Sports Industry Based on Chaos Theory

• Published in: Journal of environmental and public health Vol. 2022; no. 1; p. 1060639
• Main Authors: Luo, Yuankai, Gao, Shanshan, Yan, Xuanfei, Cao, Yecheng
• Format: Journal Article
• Language: English
• Published: New York Hindawi 2022; John Wiley & Sons, Inc
• Subjects: Agglomeration; Algorithms; Analysis; Chaos theory; Chemical reactions; Cluster analysis; Data integration; Data management; Data processing; Decision analysis; Decision making; Decision theory; Education; Engineering; Extreme values; Fault diagnosis; Genetic algorithms; Indicators; Industrial development; Interdisciplinary subjects; Kalman filters; Mathematical analysis; Neural networks; Optimization; Public health; Questionnaires; Simulation analysis; Spatial distribution; Sports; Sustainable development; Iran; China
• ISSN: 1687-9805; 1687-9813; 1687-9813
• DOI: 10.1155/2022/1060639

The sports industry is an emerging industry with broad development prospects, and it is also full of competition. The sports industry has the characteristics of fluctuation, intermittence, and randomness, which are suitable for the analysis of chaos theory in order to find out the internal development law of the sports industry. In order to solve the above problems, an improved chaos theory method is proposed in this paper and the K-cluster analysis method is integrated into chaos calculation, in order to reduce the occurrence rate of the “local extreme value” and improve the accuracy of calculation results. The model uses nonlinear and irregular chaos theory to analyze the aggregation degree of sports industry, industrial spatial distribution, and the spatial governance effect and find out the best optimization decision. When selecting the optimization indicators, not only the European distance of each indicator cluster but also the spatial correlation of the indicators are considered to realize the comprehensive analysis of the sports industry and improve the accuracy of optimization. In the simulation analysis of optimization decision-making, the decision-making model based on chaos theory is compared with the previous first-order decision-making model. The results show that the improved chaos theory can control the data aggregation range of sports industry between (0∼3), the data fusion degree of industrial space between 95 and 99%, and the variation range between 0 and 0.2%, which is significantly better than (0∼9), 90∼95%, and 0∼0.4% of the genetic algorithm. Therefore, the aggregation degree, spatial governance, and decision optimization of the optimization decision-making model proposed in this paper are better than those of the previous genetic algorithm.