DocumentCode :
2694622
Title :
Training type-2 Fuzzy System by particle swarm optimization
Author :
Al-Jaafreh, Moha Med O ; Al-Jumaily, Adel A.
Author_Institution :
Univ. of Technol., Sydney
fYear :
2007
fDate :
25-28 Sept. 2007
Firstpage :
3442
Lastpage :
3446
Abstract :
Many intelligent techniques were established during last decades to handle nonlinear, multimode, noisy, nondifferentiable problems and to obtain optimum solution(s). This paper presents improving and implementations for two recently intelligent techniques; type-2 fuzzy system (T2 FS) and particle swarm optimization (PSO) and presents a new method to optimize parameters of the primary membership functions of T2 FS by PSO to improve the performance and increase the accuracy of T2 FS model. The implementation of the suggested method on mean blood pressure estimation has very successful rate.
Keywords :
fuzzy set theory; particle swarm optimisation; intelligent techniques; membership functions; particle swarm optimization; type-2 fuzzy system; Evolutionary computation; Fuzzy systems; Particle swarm optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1339-3
Electronic_ISBN :
978-1-4244-1340-9
Type :
conf
DOI :
10.1109/CEC.2007.4424917
Filename :
4424917
Link To Document :
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