Design of intelligent examination system based on convolutional neural network
At present,too many educational examination information systems in various regions is not con-ducive to the intelligent reform and development of education.To solve the above problems,an intelligent examination system is designed.An association algorithm based on convolutional neural networks(CNN)is designed to associate the multiple information of each educational examination information system,and com-bined with CNN and the long short-term memory artificial neural network(LSTM),a granularity calculation algorithm is designed to fuse multi granularity features of examination data.The experiment results show that the accuracy of the intelligent examination system in the three levels of word granularity,word granularity and multi granularity feature fusion is 90.2％,91.4％and 93.7％respectively,which can improve the u-tilization rate of the information of the examination information system and provide data support for the infor-mation development of local education.
CNNLSTMdata fusionmulti granularityexamination system
万方数据
维普
