Simulation of intelligent allocation model of local cultural and educational resources based on improved particle swarm optimization algorithm

Abstract

With the continuous development of society, the distribution of cultural and educational resources has become a concern, which is related to the quality of local cultural heritage and education popularization. Traditional resource allocation methods usually have some problems, such as low efficiency, obvious inequality and difficulty in dealing with uncertainty. In order to meet these challenges, this study introduces an improved Particle Swarm Optimization(PSO) algorithm, and constructs an intelligent allocation model of local cultural and educational resources based on adaptive PSO to optimize the allocation of cultural and educational resources. Through the simulation experiment based on real data, this study verifies the effectiveness of the improved PSO algorithm in the allocation of local cultural and educational resources. The results show that the improved PSO algorithm not only improves the efficiency of resource utilization, but also optimizes the resource allocation strategy and reduces the occurrence of inequality. The algorithm also responds to the uncertainty well, which is expected to provide strong support for the intelligent allocation of local cultural and educational resources.