Fuzzy control based on genetic algorithm in intelligent psychology teaching system

Abstract

The advancement of science has made computer technology and the education industry more and more closely related, and the development of intelligent teaching systems has also opened a new path for classroom teaching. This paper studies the application of fuzzy control based on genetic algorithms in the intelligent psychology teaching system. Facing the complicated variables in the teaching process, the improved genetic algorithm can better realize dynamic teaching decisions through fuzzy control. This article aims to improve the quality of psychology classroom teaching, and develops an intelligent psychology teaching system based on the fuzzy control theory of genetic algorithm. Combined with the current development of fuzzy control theory, the problems existing in the intelligent teaching system are studied and analyzed, and they have been optimized and improved. This paper proposes a control algorithm based on a teaching management system. The algorithm can implement fuzzy control on student models, knowledge organization structure, intelligent test papers and teaching decision-making. While restoring the real teaching process, it can better realize teaching students in accordance with their aptitude and improve teaching. The intelligence of the system. According to the system test data, the proportions of the difficulty of the system’s automatic test paper are 30.1%, 51.6%, 18.3%, which are in line with the designer’s set expectation of 3 : 5:2, which shows the improved genetic algorithm. It can realize the intelligent volume group function very well.