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Proceedings Paper

Knowledge manipulation in a Hebbian network for fault diagnosis
Author(s): Da Deng; Shuang Li
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Paper Abstract

Recently research on hybrid solutions for fault diagnosis problems. In this paper we propose a neural network implementation of diagnosis systems. Based on certainty factor modeling and Hebbian learning, the network features with local learning ability, quasi-causal representation of diagnosis process, and easy mechanism of knowledge manipulation.

Paper Details

Date Published: 25 March 1998
PDF: 8 pages
Proc. SPIE 3390, Applications and Science of Computational Intelligence, (25 March 1998); doi: 10.1117/12.304799
Show Author Affiliations
Da Deng, South China Univ. of Technology (China)
Shuang Li, Guangzhou Univ. (China)


Published in SPIE Proceedings Vol. 3390:
Applications and Science of Computational Intelligence
Steven K. Rogers; David B. Fogel; James C. Bezdek; Bruno Bosacchi, Editor(s)

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