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A Novel Approach to Fuzzy Model Identification Based on Bat Algorithm

Author

Listed:
  • Neety Bansal

    (Maharishi Markandeshwar University, Haryana, India)

  • Parvinder Kaur

    (Chandigarh College of Engineering and Technology, Degree Wing, Chandigarh, India)

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.

Suggested Citation

  • Neety Bansal & Parvinder Kaur, 2019. "A Novel Approach to Fuzzy Model Identification Based on Bat Algorithm," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 10(2), pages 93-108, April.
    • Handle: RePEc:igg:jamc00:v:10:y:2019:i:2:p:93-108
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