Construction of Ideological Education Evaluation System for College Students -- Based on BP Neural Network Model Algorithm

• Published in: Journal of physics. Conference series Vol. 1852; no. 4; p. 42074
• Main Author: Liu, Guangxin
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.04.2021
• Subjects: Algorithms; Artificial neural networks; Back propagation; College students; Colleges & universities; Computer simulation; Education; Ideology; Mathematical analysis; Model accuracy; Neural networks; Physics; Students
• ISSN: 1742-6588; 1742-6596; 1742-6596
• DOI: 10.1088/1742-6596/1852/4/042074

Because of the characteristics of Ideological Education, it cannot be expressed accurately by simple mathematical analysis like other disciplines. The emergence of artificial neural network can solve this problem, but there are not many researches about BPNN (BP neural network) in the evaluation system of Ideological Education in Colleges and universities. Therefore, this paper puts forward the construction of Ideological Education evaluation system for college students --- Based on BPNN model algorithm research. In this paper, the existing Ideological Education in Colleges and universities and the application of BPNN in the evaluation system of Ideological Education are deeply studied. It is considered that the existing evaluation system of Ideological Education has some technical problems such as large evaluation error. In view of this, according to the actual needs of Ideological Education evaluation in Colleges and universities, combined with the latest BPNN technology, this paper establishes a new evaluation system of Ideological Education in Colleges and Universities Based on BPNN. This paper optimizes the traditional BPNN algorithm, simplifies the calculation steps and improves the calculation accuracy of the model. In order to further verify the actual effect of the evaluation model in this paper, the relevant comparative experiments are carried out, and the simulation results are analyzed by comparing with the expert evaluation. The experimental results show that the error value of the simulation results of the evaluation model in this paper is kept below 1.5%, and the accurate value is within the acceptable range, which can meet most of the current Ideological Education evaluation needs.