Research on auxiliary decision-making method of online public opinion in emergencies based on neutrosophic number
In order to solve the problem that most of the current research on emergency decision-making focus on the con-struction of mathematical models,and the decision data is biased towards subjective assumptions,which leads to the lack of objectivity,practicality and intelligence,an intelligent acquisition method of single-valued neutrosophic number based on deep learning and emotional tendency analysis was proposed and applied to the emergency decision-making.Firstly,the Python pro-gramming technology was used to carry out the capture,preprocess,statistical analysis and visualization of online public opin-ion data of emergencies,and the quantified single-valued neutrosophic number was obtained.Secondly,the attribute weights were determined objectively based on the exact function and information entropy by using the uncertainty characteristic of the neutrosophic number itself.Finally,the case-based reasoning(CBR)method was used to rank and prioritize the alternatives.The results show that the proposed method can monitor the online public opinion of emergencies in real time,obtain the deci-sion data objectively and intelligently,thus realize the quantitative evaluation of typhoon disaster.The research results can provide intelligent auxiliary decision-making support for relevant departments to effectively cope with the online public opinion in emergencies.
emergenciesonline public opinionemergency decision-makingdata analysisneutrosophic numbercase-based reasoning
万方数据
维普
