Research on School Classroom Teaching Model Based on Clustering Algorithm and Fuzzy Control

Abstract

The method of computational intelligence to monitor and evaluate the concentration of students in the teaching process can promptly and effectively adjust the learning plan and improve the learning effect. In this article, clustering algorithm and fuzzy control methods are used to construct a research model of students’ attention in class. In addition, this article uses the existing MATLAB-based image feature recognition algorithm to detect and obtain facial features and analyze the main features of facial expressions through computational techniques to realize the judgment of attention. In addition, this article optimizes the traditional AdaBoost algorithm to save computing time and improve operating efficiency and system performance stability. Finally, this article constructs the functional modules of the research model according to actual needs and designs experiments to verify the performance of the model. Experimental research results show that the model constructed in this article has a certain effect.