@inproceedings{64ca0ad932e748d1b27c07a26c034634,
title = "Research on public opinion warning based on analytic hierarchy process integrated back propagation neural network",
abstract = "Food safety is one of the hot issues in all over the world. It is related to national economy and people's livelihood. In recent years, food safety accidents occur in China frequently, so an effective food safety network public opinion early warning model is necessary and imperative. Therefore, the model of Back Propagation neural network based on Analytic Hierarchy Process (AHP-BP) is proposed. The AHP method is used to fuse the indicators of microblogging and news to get the four types of warning levels. The fusion data are set as the expected output of the BP neural network. And then the indicators of microblogging and news are set as the input of the BP neural network. Finally, this proposed model is applied in food safety field. Several food safety incidents show that the AHP-BP model can effectively control the diffusion and dissemination of sensitive information, which means the practicability and effectiveness of the proposed model.",
keywords = "early warning, food safety, model, nerual network, network public opinion",
author = "Shunzi Li and Yuan Xu and Yanlin He and Zhiqiang Geng and Zhiying Jiang and Qunxiong Zhu",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 Chinese Automation Congress, CAC 2017 ; Conference date: 20-10-2017 Through 22-10-2017",
year = "2017",
month = dec,
day = "29",
doi = "10.1109/CAC.2017.8243185",
language = "English",
series = "Proceedings - 2017 Chinese Automation Congress, CAC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2440--2445",
booktitle = "Proceedings - 2017 Chinese Automation Congress, CAC 2017",
address = "United States",
}