Simulation of Industrial Economic Development Model Based on Fuzzy Clustering Algorithm

As human society enters the era of the knowledge economy, the "industrial economic development of Fuzzy Clustering Algorithm (FCM), which promotes the development of science and technology and social progress, has undergone profound changes in both connotation and form, and has gradually become an important part of the national development strategy." In order to investigate the effects of various policy alternatives on the energy industry, a system simulation model of the expansion of the energy industry from the position of a low-carbon economy is created based on DPSIR theory from the perspectives of energy, economy, environment, policy, and society. There are other clustering algorithms available today, but the fuzzy c-means clustering algorithm is the most widely used. Many improved techniques are presented based on this algorithm to produce a better clustering effect. The clustering effectiveness index must be evaluated for the effect after clustering. Clustering analysis is a critical component of unsupervised pattern recognition. Fuzzy clustering has become the industry standard for clustering analysis because it establishes the ambiguous description of the sample for the category and can more precisely reflect reality.