| Issue |
MATEC Web Conf.
Volume 63, 2016
2016 International Conference on Mechatronics, Manufacturing and Materials Engineering (MMME 2016)
|
|
|---|---|---|
| Article Number | 04007 | |
| Number of page(s) | 5 | |
| Section | Information Technology, Control and Application | |
| DOI | https://doi.org/10.1051/matecconf/20166304007 | |
| Published online | 12 July 2016 | |
Evaluation of Psychological Impact of Emergency Events Based on Bayesian Network
1 School of Economics and Management, and School of Science, Yanshan University Qinhuangdao, China
2 School of Economics and Management, Yanshan University, Qinhuangdao, China
a Corresponding author: songzhj@ysu.edu.cn
Representation and inference of uncertain knowledge pose great challenge to the evaluation of the impact of emergency events on public psychology. With the advantages in solving issues on an uncertain basis, Bayesian network exhibits a superioty in effectively coping with the diversity, uncertainty and ambiguity of the evaluative information of emergency events. A model was established in this article to evaluate the impact caused by emergency events on the public’s psychological health based on the Bayesian network. Moreover, the method of inference and decision-making was also presented, and an example analysis was performed. The result shows that the proposed model can improve the evaluation accuracy and the responsiveness of the managers when making decisions.
Key words: Bayesian network / emergency events / public psychology / impact degree
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.