A Novel Approach to Fuzzy Model Identification Based on Bat Algorithm

The identification of a fuzzy model is a complex and nonlinear problem. This can be formulated as a search and optimisation problem and many computing approaches are available in the literature to solve this problem. This research paper is focused on using a new nature inspired approach for fuzzy mo...

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Published inInternational journal of applied metaheuristic computing Vol. 10; no. 2; pp. 93 - 108
Main Authors Bansal, Neety, Kaur, Parvinder
Format Journal Article
LanguageEnglish
Published IGI Global 01.04.2019
Subjects
Algorithms
Analysis
India
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ISSN1947-8283
1947-8291
DOI10.4018/IJAMC.2019040104

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Abstract The identification of a fuzzy model is a complex and nonlinear problem. This can be formulated as a search and optimisation problem and many computing approaches are available in the literature to solve this problem. This research paper is focused on using a new nature inspired approach for fuzzy modeling based on Bat Algorithm which is derived from the behaviour of micro-bats to search for their prey. The bat algorithm approach has been implemented and validated successfully on a rapid battery charger fuzzy controller problem. Currently, the key requirement is real-time solutions to complex problems at a blazing speed. Bat algorithm evolved the optimised fuzzy model within a few seconds as compared to other approaches.
AbstractList The identification of a fuzzy model is a complex and nonlinear problem. This can be formulated as a search and optimisation problem and many computing approaches are available in the literature to solve this problem. This research paper is focused on using a new nature inspired approach for fuzzy modeling based on Bat Algorithm which is derived from the behaviour of micro-bats to search for their prey. The bat algorithm approach has been implemented and validated successfully on a rapid battery charger fuzzy controller problem. Currently, the key requirement is real-time solutions to complex problems at a blazing speed. Bat algorithm evolved the optimised fuzzy model within a few seconds as compared to other approaches.
Audience Academic
Author Bansal, Neety
Kaur, Parvinder
AuthorAffiliation Maharishi Markandeshwar University, Haryana, India
Chandigarh College of Engineering and Technology, Degree Wing, Chandigarh
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  organization: Chandigarh College of Engineering and Technology, Degree Wing, Chandigarh
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Title A Novel Approach to Fuzzy Model Identification Based on Bat Algorithm
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