Research on University Network Public Opinion Prediction Based on Dynamic Membrane Neural Network
[Purpose/significance]University network public opinion prediction plays an important role in university emergency management.Correct predictive analysis can provide a basis for the guidance and management of public opinion,and plays an important role and significance in enhancing the ability of universities to respond to network public opinion and maintaining the harmony and stability of universities.[Method/process]Applying the structure and operation of the cellular P system,as well as the rules of the membrane algorithm,combined with the genetic algorithm to design dynamic operators,the LSTM neural network is optimized,and the long and short-term memory neural network prediction model based on dynamic membrane drive(DM-LSTM)is obtained to carry out the research on the prediction of network public opinion in universities.[Result/conclusion]This paper proposes a long and short-term memory neural network prediction model based on dynamic membrane driving(DM-LSTM).Through empirical research and comparative analysis,it is proved that the proposed DM-LSTM model has better superiority and stability in terms of prediction accuracy and algorithm performance.
LSTMuniversity network public opinionmembrane algorithmprediction research
万方数据
维普
