1. Traffic accidents inference based on Bayesian networks
- Author
-
Xiangyang Cheng and Fangda Cui
- Subjects
Markov chain ,Computer science ,business.industry ,Bayesian probability ,Bayesian network ,Markov process ,computer.software_genre ,Machine learning ,Causal Markov condition ,Variable-order Bayesian network ,Bayesian statistics ,symbols.namesake ,symbols ,Data mining ,Artificial intelligence ,business ,computer ,Dynamic Bayesian network - 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.
- Published
- 2011