Title :
An Improved Bayesian Network Inference Algorithm
Author_Institution :
Inst. of Sci. & Tech. Inf. of China, Beijing, China
Abstract :
In the on-line fault diagnosis of auto engineer before factory in FAW, we adopt Bayesian network inference to get diagnosis result. To reduce inference complexity, an improved Bayesian network inference algorithm is presented based on graph search strategy under Martelli standard. Through proof, the complexity of the improved algorithm can reduce from exponential level to polynomial level. In experiment, the algorithm has been realized and been compared with expert system method, the experiment shows that the improved algorithm can improve the diagnosis efficiency. The algorithm has been applied in the on-line fault diagnosis of auto engineer before factory in FAW successfully.
Keywords :
automotive engineering; belief networks; computational complexity; expert systems; fault diagnosis; graph theory; inference mechanisms; production engineering computing; search problems; Bayesian network; Martelli standard; auto engineer; expert system method; graph search strategy; inference algorithm; inference complexity; online fault diagnosis; Bayesian network inference; Martelli standard; polynomial level algorithm complexity;
Conference_Titel :
Intelligent Networks and Intelligent Systems (ICINIS), 2010 3rd International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-8548-2
Electronic_ISBN :
978-0-7695-4249-2
DOI :
10.1109/ICINIS.2010.183