Abstract
We describe in this paper the Bat Algorithm and a new proposed approach using interval type-2 fuzzy systems to dynamically adapt its parameters. The Bat Algorithm (denoted in the literature as BA) is a metaheuristic inspired in micro bats based on echolocation. We analyze in detail the behavior of this proposed modification using interval type-2 fuzzy logic and compare it with type-1 fuzzy logic to compare the performance of the proposed new algorithm based on the behavior of the mega bat.
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Acknowledgment
We would like to express our gratitude to the CONACYT and Tijuana Institute of Technology for the facilities and resources granted for the development of this research.
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Pérez, J., Valdez, F., Castillo, O. (2017). Modification of the Bat Algorithm Using Type-2 Fuzzy Logic for Dynamical Parameter Adaptation. In: Melin, P., Castillo, O., Kacprzyk, J. (eds) Nature-Inspired Design of Hybrid Intelligent Systems. Studies in Computational Intelligence, vol 667. Springer, Cham. https://doi.org/10.1007/978-3-319-47054-2_23
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DOI: https://doi.org/10.1007/978-3-319-47054-2_23
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