Students’ Comprehensive Quality Evaluation Based on BP Neural Network Optimized by Genetic Algorithm

Abstract

It is well known that education is No. 1 important for a country. But only good academic performance cannot meet the needs of the current society. A country needs comprehensive talents. This paper introduces the basic principle of a BP neural network optimized by genetic algorithm (GA-BP). And also, the paper proposes a students’ comprehensive quality evaluation model based on the optimized BP neural network. The model is implemented by MATLAB. The experiment result shows that the model has the advantages of fewer iterations, high convergence speed and strong generalization ability. It enables students’ comprehensive quality evaluating faster and more accurate