Optimal allocation of innovation and entrepreneurship education resources for local normal education majors based on PSO algorithm

Mingxin Qin, Yanan Yang
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Abstract

Under the background of modern education innovation, in order to ensure the university innovation entrepreneurship education resources get reasonable configuration, practice application to maximize benefits, the current research scholars to build the education resources input and output of the evaluation index system, and proposed the corresponding function model, need to use particle swarm optimization algorithm for the simulation analysis. The final experimental results show that the allocation analysis using particle swarm optimization algorithm can further improve the application efficiency of innovation and entrepreneurship education resources in colleges and universities, ensure the results of resource allocation, and provide an effective basis for the innovation of modern college education.
基于粒子群算法的地方师范专业创新创业教育资源优化配置
在现代教育创新背景下,为了保证高校创新创业教育资源得到合理配置,实践应用实现效益最大化,目前研究学者构建了教育资源投入与产出的评价指标体系,并提出了相应的功能模型,需要使用粒子群优化算法进行仿真分析。最终实验结果表明,利用粒子群优化算法进行配置分析,可以进一步提高高校创新创业教育资源的应用效率,保证资源配置效果,为现代高校教育创新提供有效依据。
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