DocumentCode :
2306187
Title :
Importance sampling based defuzzification for general type-2 fuzzy sets
Author :
Linda, Ondrej ; Manic, Milos
Author_Institution :
Comput. Sci. Dept., Univ. of Idaho, Idaho Falls, ID, USA
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
7
Abstract :
General type-2 fuzzy logic systems (T2 FLS) constitute a powerful tool for coping with ubiquitous uncertainty in many engineering applications. However, the immense computational complexity associated with defuzzification of general T2 fuzzy sets still remains an unresolved issue and prohibits its practical use. This paper proposes a novel importance sampling based defuzzification method for general T2 FLS. Here, a subset from the domain of all embedded fuzzy sets is randomly sampled using a specific probability distribution function. The algorithm is compared with the previously published uniform sampling defuzzification method. Experimental results demonstrate that importance sampling substantially reduces the variance of the sampling defuzzification method. Comparison of T2FLS output surfaces showed that smoother and more stable response can be achieved with the proposed importance sampling based defuzzification method.
Keywords :
computational complexity; fuzzy logic; fuzzy set theory; importance sampling; uncertainty handling; computational complexity; defuzzification; importance sampling; type-2 fuzzy logic systems; type-2 fuzzy sets; ubiquitous uncertainty; Frequency selective surfaces; Fuzzy sets; Monte Carlo methods; Probability distribution; Random variables; Testing; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems (FUZZ), 2010 IEEE International Conference on
Conference_Location :
Barcelona
ISSN :
1098-7584
Print_ISBN :
978-1-4244-6919-2
Type :
conf
DOI :
10.1109/FUZZY.2010.5584256
Filename :
5584256
Link To Document :
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