An optimized BP neural network model for teaching management evaluation

Issue title: Artificial Intelligence as a maturing and growing technology: An urgent need for intelligent systems

Guest editors: X. Yuan and M. Elhoseny

Article type: Research Article

Authors: Yang, XinShun | Zhou, JiaJia | Wen, DaoQun^{; *}

Affiliations: Chongqing Chemical Industry Vocational College

Correspondence: [*] Corresponding author. DaoQun Wen, Chongqing Chemical Industry Vocational College. E-mail: cqhg127@163.com.

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.

Keywords: Teaching management evaluation, particle swarm optimization, BP neural network, normal distribution, weight, threshold value

DOI: 10.3233/JIFS-189361

Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3215-3221, 2021