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
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;
Conference_Titel :
Multimedia Technology (ICMT), 2011 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-61284-771-9
DOI :
10.1109/ICMT.2011.6001723