Volume 5 Number 6 (Jun. 2010)
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JCP 2010 Vol.5(6): 828-835 ISSN: 1796-203X
doi: 10.4304/jcp.5.6.828-835

A Study of Fault Diagnostic based on Artifcial Immune Systems

Chu-Jiao Wang1, Shi-Xiong Xia1, and Hai-zhi Wang2
1 School of Computer Science and Technology China University of Mining and Technology Xu Zhou, China
2 Marine Engineering Institute JiMei University Xia Men, China


Abstract—Artificial Immune technology, a resource limited artificial immune classifier system,has performed well on elementary classification tasks. This paper presents one form of mapping Artificial Immune Systems (AIS) into Learning Classifier Systems for fault diagnosis. We propose a novel ideal to apply semantics in immune models. Similar to Learning Classifier Systems, a better understanding of AIS can be obtained when they are analysed under the perspective of complex Semantic system. One of the goals here is to determine complementary features of both systems (Semantic systemand AIS), aiming at providing a novel mapping conception for fault diagnosis. Our motivation comes from the use of a semantic structure for diagnosis of mine hoist based AIS.

Index Terms—fault diagnosis; semantic structure; Artificial Immune Systems; System modelling

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Cite: Chu-Jiao Wang, Shi-Xiong Xia, and Hai-zhi Wang, " A Study of Fault Diagnostic based on Artifcial Immune Systems," Journal of Computers vol. 5, no. 6, pp. 828-835, 2010.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Monthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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