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A Novel Approach to Fuzzy Model Identification Based on Bat Algorithm

A Novel Approach to Fuzzy Model Identification Based on Bat Algorithm

Neety Bansal, Parvinder Kaur
Copyright: © 2019 |Volume: 10 |Issue: 2 |Pages: 16
ISSN: 1947-8283|EISSN: 1947-8291|EISBN13: 9781522566076|DOI: 10.4018/IJAMC.2019040104
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MLA

Bansal, Neety, and Parvinder Kaur. "A Novel Approach to Fuzzy Model Identification Based on Bat Algorithm." IJAMC vol.10, no.2 2019: pp.93-108. http://doi.org/10.4018/IJAMC.2019040104

APA

Bansal, N. & Kaur, P. (2019). A Novel Approach to Fuzzy Model Identification Based on Bat Algorithm. International Journal of Applied Metaheuristic Computing (IJAMC), 10(2), 93-108. http://doi.org/10.4018/IJAMC.2019040104

Chicago

Bansal, Neety, and Parvinder Kaur. "A Novel Approach to Fuzzy Model Identification Based on Bat Algorithm," International Journal of Applied Metaheuristic Computing (IJAMC) 10, no.2: 93-108. http://doi.org/10.4018/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.

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