Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/7822
Title: Weighted fuzzy interpolative reasoning method
Authors: Li, YM
Huang, DM
Tsang, ECC
Zhang, LN
Keywords: Fuzzy set theory
Inference mechanisms
Knowledge based systems
Issue Date: 2005
Publisher: IEEE
Source: Proceedings of 2005 International Conference on Machine Learning and Cybernetics, 2005, 18-21 August 2005, Guangzhou, China, v. 5, p. 3104-3108 How to cite?
Abstract: Interpolative reasoning method is a reasoning technique, which is designed to deal with reasoning in sparse rule-based systems. This paper proposed a weighted fuzzy interpolative reasoning method by using a like-gravity-centre of fuzzy sets whose shapes are trapezoidal. This method allows the conditions appearing in the antecedent part and the consequence of the rules, the certainty factors of the rules, and the weights of the conditions appearing in the antecedent part of the rules to be represented by trapezoidal fuzzy numbers. We use scale and move rate transformation operation to support such reasoning. The presented method are constructing a new inference rule first by manipulating two given adjacent rules and next by exploiting similarity information to convert the derived inference result into the conclusion.
URI: http://hdl.handle.net/10397/7822
ISBN: 0-7803-9091-1
DOI: 10.1109/ICMLC.2005.1527475
Appears in Collections:Conference Paper

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