NDLI: Recent advances on the use of meta-heuristic optimization algorithms to optimize the type-2 fuzzy logic systems in intelligent control

Content Provider	Springer Nature Link
Author	Hamza, Mukhtar Fatihu Yap, Hwa Jen Choudhury, Imtiaz Ahmed
Copyright Year	2015
Abstract	Finding the appropriate values of parameters and structure of type-2 fuzzy logic systems is a difficult and complex task. Many types of meta-heuristic algorithms have been used to find the complex structure and appropriate parameter values of the type-2 fuzzy systems and more recently hybrid meta-heuristic algorithms. In this paper, we review recent advances (2012 to date) on the application of meta-heuristic algorithms and hybrid meta-heuristic algorithms, for the optimization of type-2 fuzzy logic systems in intelligent control. It was found that the major meta-heuristic algorithms used for optimizing the design of type-2 fuzzy logic systems in intelligent control were genetic algorithms and particle swarm optimization as well as hybrid meta-heuristic algorithms. Researchers can use this review as a starting point for further advancement as well as an exploration of other meta-heuristic algorithms that have received little or no attention from researchers.
Starting Page	979
Ending Page	999
Page Count	21
File Format	PDF
ISSN	09410643
Journal	Neural Computing and Applications
Volume Number	28
Issue Number	5
e-ISSN	14333058
Language	English
Publisher	Springer London
Publisher Date	2015-11-21
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Type-2 fuzzy logic systems Intelligent control Genetic algorithm Particle swarm optimization Hybrid meta-heuristic algorithms Artificial Intelligence (incl. Robotics) Data Mining and Knowledge Discovery Probability and Statistics in Computer Science Computational Science and Engineering Image Processing and Computer Vision Computational Biology/Bioinformatics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Software

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