Affiliations: Institute of Technology, East China Jiaotong University, Jiangxi, Nanchang, China
Correspondence:
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Corresponding author. Min Wan, Institute of Technology, East China Jiaotong University, Jiangxi, Nanchang, China. E-mail: [email protected].
Abstract: The development of the economic system is affected by many factors, and the stability of the traditional economic analysis model is difficult to maintain. In order to explore the efficient and stable economic system evaluation and analysis model, based on machine learning ideas, this study uses rough set algorithm as the basic algorithm, and applies the related methods of rough set and catastrophe model theory to the evaluation of ecological economic development level. Moreover, this study reduces the redundant index of the index system and calculates the importance of the index after reduction. Based on the catastrophe set model, this study uses MATLAB software programming to comprehensively quantify the ecological economy, and finally divides the ecological economic grade. In addition, this study combines rough set theory with fuzzy mathematics, and initially establishes a two-branch fuzzy evaluation model. Finally, this study combines the actual situation to use the established model to evaluate the regional eco-economic system. The research results show that the method proposed in this paper has a certain effect, which can provide a reference for subsequent related research.
Keywords: Fuzzy set, machine learning, comprehensive evaluation, economic system
