Genetic programming with Probabilistic Model for fault detection

被引：0

作者：

Chen, DY ^{[1
]}

Zhou, YQ ^{[1
]}

Li, TS ^{[1
]}

机构：

[1] Guangxi Univ, Coll Comp Sci & Informat Engn, Nanning 530004, Peoples R China

来源：

PROCEEDINGS OF THE 11TH JOINT INTERNATIONAL COMPUTER CONFERENCE | 2005年

关键词：

Probabilistic Model; genetic programming; fault detection; electro-mechanical device; artificial neural network;

D O I：

10.1142/9789812701534_0098

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper a new method is presented to solve a series of fault detection problems using Probabilistic Model (PM) in Genetic Programming (GP). Fault detection can be seen as a problem of multi-class classification. GP methods used to solve problems have a great advantage in their power to represent solutions to complex problems, and this advantage remains true in the domain of fault detection. Moreover, diagnosis accuracy can be improved by using PM. In the end of this paper, we use this method to solve the fault detection of electro-mechanical device. The results show that the method uses GP with PM to solve fault detection of electro-mechanical device outperforms the artificial neural network (ANN).

引用

页码：434 / 437

页数：4

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