Computer Science ›› 2021, Vol. 48 ›› Issue (6A): 190-195.doi: 10.11896/jsjkx.200600094

• Big Data & Data Science • Previous Articles     Next Articles

Network Public Opinion Trend Prediction of Emergencies Based on Variable Weight Combination

CHENG Tie-jun, WANG Man   

  1. School of Economics,Nanjing University of Posts and Telecommunications,Nanjing 210023,China
  • Online:2021-06-10 Published:2021-06-17
  • About author:CHENG Tie-jun,born in 1985,Ph.D,associate professor.Her main research interest is application statistics.
    WANG Man,born in 1996,postgra-duate.Her main research interest is application statistics.
  • Supported by:
    National Social Science Foundation of China(17CXW012).

Abstract: It is of great significance for social stability to analyze and predict the development trend of network public opinions on emergencies and discover the potential crisis in the process of spreading public opinions.On the basis of Logistic curve model and BP neural network,this paper constructs a variable weight combination prediction model from the perspective of non-linear programming based on the principle of minimum sum of squared error.The experimental results of three events show that the variable weight combination forecasting model which is constructed in this paper can better solve the problem and has higher accuracy.The validity and feasibility of the model is also verified.

Key words: BP neural network, Emergencies, Logistic curve, Network public opinion, Variable weight combination prediction

CLC Number: 

  • G206
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