Model and Simulation of Maximum Entropy Neural Network for Teaching Quality Evaluation
Yingying Su · Jisuanji fangzhen · 2013
Teaching quality evaluation is important work in teaching management,the core of which is how to model the complex nonlinear relationship between many evaluation indicators and the evaluation results.The accumulation of expert experience knowledge was not considered in modeling process by BP neural network,which included uncertainty distribution information of the evaluation indicators and the evaluation results,this might lead to the model prediction accuracy of the results of the evaluation is poor and the weak performance of the model generalization.In view of this,mean square error criterion of the convention BP neural network was replaced by maximum entropy criterion which depicted the uncertainty distribution information in the paper,then this maximum entropy neural network modeling was used for education quality evaluation.Data simulation and fifty teachers' evaluation results by the model both show that the relative errors of the evaluation results are under 5% and significantly better than convention BP neural network model.It indicates that the evaluation results by the model have high credibility,and the model has good generalization performance.It provides a feasible method to accurate evaluation of teaching quality.