Network Public Opinion Prediction Based on Variational Mode Decomposition and IGJO-SVR
The prediction of the evolution trend of network public opinion has very important practical significance for the rel-evant government departments to supervise the development of public opinion and maintain the stability of public opinion in to-day's network environment.Aiming at the particularity of network public opinion data and considering the accuracy of model pre-diction results,this paper uses variational mode decomposition(VMD)and improved golden jackal optimization support vector regression(IGJO-SVR)to construct a network public opinion evolution trend prediction model,and takes'Beixi'event-related public opinion data as a case for empirical research.The comparison results show that the accuracy of the prediction model con-structed in this paper is significantly better than the other models.The network public opinion heat prediction model based on variational mode decomposition VMD and IGJO-SVR has excellent prediction accuracy,and can provide effective public opinion situation analysis and decision-making help for relevant government departments in practical work.