BP Neural Network Programming Capability Evaluation Method Based on Entropy Weight-deviation Maximization
Aiming at the problem that programming ability is difficult to evaluate in traditional teaching,a method of evaluating students'programming ability using BP neural network is proposed.The weight of each index of programming ability is obtained by combining entropy weight method and deviation maximization meth-od,and the comprehensive score of students'programming ability is calculated to optimize the input of the eval-uation model,and the input space of the model is increased by adjusting the number of hidden layers.In order to reduce the output error of the evaluation model and compare the evaluation effect of different BP neural net-works,the experimental results show that when the number of hidden layers is 2,the output error of the evalu-ation model is the smallest,and the prediction accuracy of the model is 90.91％,which can evaluate the students'programming ability.
neural network algorithmBP neural networkeducational data miningprogramming ability
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