Study on Innovation Education Evaluation for University Based on Improved BP Neural Network

Abstract

Innovation education performance management plays a key role in training innovative students for universities, and how to evaluate innovation education performance is one of the difficulties and hot research fields for the researchers related. The paper presents a new model for evaluating innovation education performance based on improved BP neural network. First an evaluation indicator system of innovation education performance is designed through the aspects of university regulation and teachers and students and education effects; Second, aiming at the shortages of the existing BP neural network algorithm of data-mining for evaluating innovation education performance, BP neural network algorithm is improved through adjusting dynamic strategy and the value of momentum factor to speed up the convergence and simplify the structure and to improve evaluating accuracy of the original BP model. Finally the experimental results show that the new evaluation indicator system and improved BP neural network algorithm can be used practically in evaluating innovation education for different universities and guarantee the evaluation effectiveness and validity.