A Novel Approach to Fuzzy Model Identification Based on Bat Algorithm

Neety Bansal and Parvinder Kaur
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Neety Bansal: Maharishi Markandeshwar University, Haryana, India
Parvinder Kaur: Chandigarh College of Engineering and Technology, Degree Wing, Chandigarh, India

International Journal of Applied Metaheuristic Computing (IJAMC), 2019, vol. 10, issue 2, 93-108

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.

Date: 2019
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International Journal of Applied Metaheuristic Computing (IJAMC) is currently edited by Peng-Yeng Yin

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