Modeling and Analysis of Train Rear-End Collision Accidents Based on Stochastic Petri Nets
Joint Authors
Wu, Chao
Cao, Chengxuan
Sun, Yahua
Li, Keping
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-09-17
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
We proposed a model of the train rear-end collision accidents based on stochastic Petri nets (SPN) theory.
By isomorphic Markov chain model of the proposed accident model, we provide the quantitative analysis of the train rear-end collision accidents.
Fuzzy random method is also applied to analyze the performance of the proposed model.
In addition, according to the data extracted from a large amount of historical data of the accident statistics, we present a case analysis and discussion.
It showed that the results of the proposed train rear-end accident model based on SPN are reasonable in practical applications and can be used to effectively analyze the accidents and prevent loss, and the results may be a reference to the department of railway safety management.
American Psychological Association (APA)
Wu, Chao& Cao, Chengxuan& Sun, Yahua& Li, Keping. 2015. Modeling and Analysis of Train Rear-End Collision Accidents Based on Stochastic Petri Nets. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1074248
Modern Language Association (MLA)
Wu, Chao…[et al.]. Modeling and Analysis of Train Rear-End Collision Accidents Based on Stochastic Petri Nets. Mathematical Problems in Engineering No. 2015 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1074248
American Medical Association (AMA)
Wu, Chao& Cao, Chengxuan& Sun, Yahua& Li, Keping. Modeling and Analysis of Train Rear-End Collision Accidents Based on Stochastic Petri Nets. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1074248
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074248