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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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References

  1. Duda, P.O., Hart, P.E.: Pattern classification and scene analysis. Wiley, New York (1973)

    MATH  Google Scholar 

  2. Albus, J.S.: A new approach to manipulator control: the cerebellar model articulation controller (CMAC). J. Dyn. Syst. Meas. Control Trans. ASME 97, 220–227 (1975)

    Article  MATH  Google Scholar 

  3. Lin, C.T., Lee, C.S.G.: Neural Fuzzy systems: A Neuro-Fuzzy Synergism to Intelligent Systems. Prentice-Hall, Upper Saddle River (1996)

    Google Scholar 

  4. Lee, C.Y., Lin, C.J., Chen, H.J.: A self-constructing fuzzy CMAC model and its applications. Inf. Sci. 177(1), 264–280 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  5. Holland, J.H.: Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor (1975)

    Google Scholar 

  6. Dorigo, M., Caro, G.D.: Ant colony optimization: a new meta-heuristic. In: Proceedings of the 1999 Congress on Evolutionary Computation, CEC 99, vol. 2, pp. 1470–1477 (1999)

  7. Kennedy, J., Eberhart, R.: Particle swarm optimization. IEEE Int. Conf. Neural Netw. 4, 1942–1948 (1995)

    Google Scholar 

  8. Storn, R., Price, K.: Differential evolution—a simple and efficient heuristic for global optimization over continuous spaces. J. Global Optim. 11(4), 341–359 (1997)

    Article  MATH  MathSciNet  Google Scholar 

  9. Passino, K.M.: Biomimicry of bacterial foraging for distributed optimization and control. IEEE Control Syst. Mag. 22(3), 52–67 (2002)

    Article  MathSciNet  Google Scholar 

  10. Yan, X., Zhu, Y., Chen, H., Zhang, H.: Improved bacterial foraging optimization with social cooperation and adaptive step size. Intell. Comput. Technol. Lect. Not. Comput. Sci. 7389, 634–640 (2012)

    Google Scholar 

  11. Majhi, R., Panda, G., Majhi, B., Sahoo, G.: Efficient prediction of stock market indices using adaptive bacterial foraging optimization (ABFO) and BFO based techniques. Expert Syst. Appl. 36(6), 10097–10104 (2009)

    Article  Google Scholar 

  12. Chen, H., Zhu, Y., Hu, K.: Self-adaptation in bacterial foraging optimization algorithm. In: 3rd International Conference on Intelligent System and Knowledge Engineering, vol. 1, pp. 1026–1031 (2008)

  13. Fan, C.W., Chen, J.Y., Zhou, Y.M.: An adaptive fuzzy cerebellar model articulation controller via particle swarm optimization. In: 2nd International Conference on Education Technology and Computer (ICETC), vol. 2, pp. V2-385–V2-390 (2010)

  14. Oentaryo, R.J., Pasquier, M., Quek, C.: RFCMAC: a novel reduced localized neuro-fuzzy system approach to knowledge extraction. Expert Syst. Appl. 38(10), 12066–12084 (2011)

    Article  Google Scholar 

  15. Blake, C.L., Merz, C.J.: UCI repository of machine learning databases. Department of Information and Computer Science, University of California, Irvine (1998)

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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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