Affiliation:
1. Chongqing Chemical Industry Vocational College
Abstract
To improve the effectiveness and intelligence of university teaching management evaluation, the particle swarm optimization BP neural network algorithm is applied to the analysis of university teaching management evaluation data. BP neural network is used to model the evaluation index of teaching management, and then particle swarm optimization is used to optimize the weight and threshold of the neural network transfer function to ensure that the output of the BP neural network can obtain the global optimal solution. The experimental results show that the proposed algorithm has a good fit between the predicted value and the actual value of the evaluation object of teaching management in Colleges and universities, and has a strong promotion value.
Subject
Artificial Intelligence,General Engineering,Statistics and Probability
Reference19 articles.
1. Multi-objective particle swarm optimization based on decomposition and differential evolution [J];Fei;Control and Decision,2017
2. Trajectory optimization with particle swarm optimization for manipulator motion planning[J];Kim;IEEE transactions on industrial informatics,2017
3. A fuzzy logic approach by using particle swarm optimization for effective energy management in IWSNs[J];Collotta;IEEE Transactions on Industrial Electronics,2017
4. Image local fuzzy measurement based on BP neural network [J];Shanchun;Chinese Journal of Image Graphics,2018
5. Prediction model of end-point phosphorus content in the BOF steelmaking process based on PCA and BP neural network[J];He;Journal of Process Control,2018
Cited by
24 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献