Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/31101
Title: A fuzzy interpolative reasoning method
Authors: Huang, D
Tsang, ECC
Yeung, DS
Keywords: Fuzzy reasoning
Fuzzy set theory
Interpolation
Knowledge based systems
Issue Date: 2004
Publisher: IEEE
Source: Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004, 26-29 August 2004, v. 3, p. 1826-1830 How to cite?
Journal: Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004, 26-29 August 2004 
Abstract: Interpolative reasoning methods is a reasoning technique that is designed to deal with reasoning in sparse rule-based systems. This paper proposed a fuzzy interpolative reasoning method by using a like - gravity - center of fuzzy sets whose shapes are trapezoidal. This method allows the conditions appearing in the antecedent part and the consequence of the rules to be represented by trapezoidal fuzzy numbers. The work steps of the presented method are first constructing a new inference rule by manipulating two given adjacent rules and next by exploiting similarity information to convert the derived inference result into the conclusion. In this process, we use scale and move rate transformation operation to support such reasoning.
URI: http://hdl.handle.net/10397/31101
ISBN: 0-7803-8403-2
DOI: 10.1109/ICMLC.2004.1382073
Appears in Collections:Conference Paper

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