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Designing interval type‐2 fuzzy logic systems using an SVD‐QR method: Rule reduction
Author(s) -
Liang Qilian,
Mendel Jerry M.
Publication year - 2000
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/1098-111x(200010)15:10<939::aid-int3>3.0.co;2-g
Subject(s) - fuzzy logic , fuzzy rule , interval (graph theory) , reduction (mathematics) , computer science , algorithm , fuzzy number , type (biology) , defuzzification , mathematics , artificial intelligence , fuzzy control system , fuzzy set , ecology , geometry , combinatorics , biology
A type‐2 fuzzy logic system (FLS) can handle numerical and linguistic uncertainties, but, like a type‐1 FLS, rule explosion is one of its major disadvantages. In this paper, we present a design method which can tremendously reduce rule number for interval type‐2 fuzzy logic systems using an SVD‐QR method. The SVD‐QR method is performed after extracting two fuzzy basis function expansions from the interval type‐2 FLS. We evaluate this method by applying it to a time‐series forecasting problem in conjunction with back‐propagation training, and demonstrate that tremendous rule number reduction ratio is achieved with very little performance degradation. © 2000 John Wiley & Sons, Inc.