Abstract
This paper presents a fuzzy knowledge representation, acquisition and reasoning scheme suitable for diagnostic systems. In addition to fuzzy sets and fuzzy production rules, we propose to using proximity relations for representing the interrelationship between symptoms in the antecedence of fuzzy production rules. A systematic generation method for acquiring proximity relations is proposed. An approximate reasoning algorithm based on such representation is also shown. Application to vibration cause identification in rotating machines is illustrated. Our scheme subsumes other fuzzy set based knowledge representation and reasoning approaches when proximity relation is reduced to identity relation.
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© 1999 Springer-Verlag Berlin Heidelberg
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Wang, SL., Wu, YH. (1999). A Fuzzy Knowledge Representation and Acquisition Scheme for Diagnostic Systems. In: Imam, I., Kodratoff, Y., El-Dessouki, A., Ali, M. (eds) Multiple Approaches to Intelligent Systems. IEA/AIE 1999. Lecture Notes in Computer Science(), vol 1611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-48765-4_4
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DOI: https://doi.org/10.1007/978-3-540-48765-4_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-66076-7
Online ISBN: 978-3-540-48765-4
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