Optimal allocation of higher education resources based on fuzzy particle swarm optimization

Abstract

The development concept of higher education will have a direct impact on the development direction of higher education, because the concept usually reflects people's understanding of the law of higher education, and the current education concept restricts the scale, quality, structure and efficiency of higher education to a certain extent. Throughout the evolution of the world's higher education development concept, it has generally experienced the overall coordination of the economic growth, the internal and external laws, and the people-centered sustainable development. This paper hopes to provide effective help by joint intelligent algorithms. In this paper, the particle swarm optimization algorithm in intelligent optimization algorithm and the FCM algorithm in cluster analysis are studied in depth, and the two are merged together to propose a fuzzy clustering algorithm based on improved particle swarm optimization algorithm. The main research contents of this thesis include: Firstly, the PSO algorithm is improved, and the random search step levy flights and PSO algorithm are repeatedly called by the iterative mode by introducing the eagle strategy. After improvement, the ESPSO algorithm can achieve a balance between global search and local development, and make the particles have more satisfactory search ability and convergence effect. Then the improved PSO algorithm is integrated into the FCM algorithm to solve the above problems of the FCM clustering algorithm and improve the clustering effect. The experimental results show that the improved espso algorithm and FCM algorithm are suitable for actual data. The simulation results show that the algorithm has better clustering effect than the traditional clustering algorithm.