Research on Music Education Performance Evaluation Based on Bp Neural Network

Implementing music education performance management is an effective way to enhance the comprehensive quality education for universities, and music education performance evaluating for universities is one of the difficulties and hot research fields for the researchers related. The paper presents a new model for evaluating music education performance based on improved BP neural network. First an evaluation indicator system of music education performance is designed through analyzing the characteristics of learners’ behavior with more details; Second, aiming at the shortages of the existing BP neural network algorithm of data-mining for evaluating music education performance, immune genetic algorithm is used to correct BP neural network to speed up the convergence and simplify the structure and to improve evaluating accuracy of the original BP model. Finally the experimental results verify that the new algorithm can guarantee the effectiveness and validity of performance evaluation for music education of different universities in its engineering application.