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A Fuzzy Cerebellar Model Articulation Controller Using a Strategy-Adaptation-Based Bacterial Foraging Optimization Algorithm for Classification Applications

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Abstract

This paper proposes a fuzzy cerebellar model articulation controller using a strategy-adaptation-based bacterial foraging optimization (SABFO) algorithm to solve classification problems. A strategic approach to the chemotaxis step in the SABFO algorithm was adopted: in this approach, each virtual bacterium swims on different run-lengths, and bacterial diversity is increased. The simulation results indicated that the performance of the proposed method was more favorable than that of other methods.

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Authors and Affiliations

  1. Department of Computer Science and Information Engineering, National Chin-Yi University of Technology, Taichung, 411, Taiwan, ROC

    Hsueh-Yi Lin, Cheng-Jian Lin & Cheng-Yi Yu

  2. Department of Digital Content Application and Management, Wenzao Ursuline University of Languages, Kaohsiung, 807, Taiwan, ROC

    Chih-Feng Wu

Authors
  1. Hsueh-Yi Lin
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  2. Chih-Feng Wu
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  3. Cheng-Jian Lin
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  4. Cheng-Yi Yu
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Correspondence to Cheng-Jian Lin.

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Lin, HY., Wu, CF., Lin, CJ. et al. A Fuzzy Cerebellar Model Articulation Controller Using a Strategy-Adaptation-Based Bacterial Foraging Optimization Algorithm for Classification Applications. Int. J. Fuzzy Syst. 17, 303–308 (2015). https://doi.org/10.1007/s40815-015-0023-6

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  • DOI: https://doi.org/10.1007/s40815-015-0023-6

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