DocumentCode :
401843
Title :
An improvement to Koczy´s interpolative reasoning method based on Taylor progression
Author :
Wang, Bao-Wen ; Li, Xia ; Liu, Wen-Yuan ; Shi, Yan ; Fang, Shu-Fen
Author_Institution :
Inst. of Inf. Sci. & Eng., Yanshan Univ., Hebei, China
Volume :
4
fYear :
2003
fDate :
2-5 Nov. 2003
Firstpage :
2485
Abstract :
In the sparse fuzzy rules, the reasoning consequence cannot be obtained by the traditional fuzzy reasoning method. To tackle this problem, Koczy and Hirota have proposed a linear interpolative reasoning method. This method resolved the problem of how to derive the reasoning consequence in the sparse fuzzy rules, but the reasoning consequences by this method sometimes become abnormal fuzzy sets [Y. Shi et al., 1995; Y. Shi & M. Mizumoto, 1997]. In order to guarantee "if fuzzy rules A1≥B1, A2≥B2 and the observation A* are defined by triangular membership functions, then the interpolated conclusion B* is linearity and convexity", we shall propose the interpolative method based on Taylor progression.
Keywords :
fuzzy logic; fuzzy systems; inference mechanisms; interpolation; uncertainty handling; Taylor progression; abnormal fuzzy sets; interpolative reasoning method; linear interpolative reasoning method; sparse fuzzy rules; triangular membership functions; Artificial intelligence; Bismuth; Cybernetics; Engineering management; Euclidean distance; Fuzzy reasoning; Fuzzy sets; Fuzzy systems; Management information systems; Technology management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
Type :
conf
DOI :
10.1109/ICMLC.2003.1259930
Filename :
1259930
Link To Document :
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