Analysis of factors that influence hazardous material transportation accidents based on Bayesian networks: A case study in China
Abstract
In this study, we applied Bayesian networks to prioritize the factors that influence hazardous material (Hazmat) transportation accidents. The Bayesian network structure was built based on expert knowledge using Dempster–Shafer evidence theory, and the structure was modified based on a test for conditional independence. We collected and analyzed 94 cases of Chinese Hazmat transportation accidents to compute the posterior probability of each...
Paper Details
Title
Analysis of factors that influence hazardous material transportation accidents based on Bayesian networks: A case study in China
Published Date
Apr 1, 2012
Journal
Volume
50
Issue
4
Pages
1049 - 1055
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
Notes
History