DocumentCode
3022876
Title
Traffic accidents inference based on Bayesian networks
Author
Cui, Fangda ; Cheng, Xiangyang
Author_Institution
Sch. of Math. & Comput. Sci., Fuyang Teachers´´ Coll., Fuyang, China
fYear
2011
fDate
26-28 July 2011
Firstpage
6151
Lastpage
6155
Abstract
Bayesian network is a graphics mode which is used to show joint probability distribution. It reflects the potential dependence relationship among variables. The Bayesian network has already been the powerful tool to solve various uncertain questions. This thesis collects some information about traffic accidents in a city of Anhui Province. According to the information, it gets the Markov network firstly. Secondly, it gives directions to all edges of the Markov network according to the mutual degree of dependence. Finally, it reaches the Bayesian network which shows the relationship of uncertain factors in traffic accidents.
Keywords
Markov processes; accidents; belief networks; probability; road safety; traffic engineering computing; Anhui Province; Bayesian networks; Markov network; graphics mode; probability distribution; traffic accidents inference; Accidents; Bayesian methods; Educational institutions; Information theory; Markov random fields; Research and development; Bayesian network; Markov network; conditional independence;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia Technology (ICMT), 2011 International Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-61284-771-9
Type
conf
DOI
10.1109/ICMT.2011.6001723
Filename
6001723
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