Early warning method of power supply enterprise service network public opinion based on fuzzy reasoning

Qianqian Li; Wenjie Fan; Xiaozhou Shen; Jing Li

doi:10.1117/12.2667502

22 February 2023 Early warning method of power supply enterprise service network public opinion based on fuzzy reasoning

Qianqian Li, Wenjie Fan, Xiaozhou Shen, Jing Li

Author Affiliations +

Proceedings Volume 12587, Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022); 1258717 (2023) https://doi.org/10.1117/12.2667502
Event: Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022), 2022, Shanghai, China

Abstract

To improve the accuracy of the power supply enterprise service network public opinion crisis early warning, the fuzzy reasoning theory is introduced to carry out the design research of the power supply enterprise service network public opinion early warning method. Based on public opinion topic intensity, development heat and public attitude, the power supply enterprise service network public opinion early warning index system is constructed. Combined with fuzzy reasoning theory, the index membership degree and early warning level membership degree are calculated. Through the learning method, the public opinion early warning level judgment rule is learned, and the public opinion early warning level judgment and early warning display are completed. The experiment proves that the new public opinion early warning method can accurately judge the degree of public opinion crisis, and give a reasonable and intuitive early warning display result.

Citation Download Citation

Qianqian Li, Wenjie Fan, Xiaozhou Shen, and Jing Li "Early warning method of power supply enterprise service network public opinion based on fuzzy reasoning", Proc. SPIE 12587, Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022), 1258717 (22 February 2023); https://doi.org/10.1117/12.2667502

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