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A Novel Approach for Combining Fuzzy Rules Using Mean Operators for Effective Rule Reduction

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Abstract

This paper will present a novel method based on harmonic mean, geometric mean, arithmetic mean and root mean square to help reduce fuzzy rules. The objective of the new method proposed is to produce fuzzy models with both a small number of interpretable rules and sufficiently high precision. Comparisons will be made between systems utilizing reduced rules and original rules to verify efficacy of the new methods in terms of the defuzzified outputs. As a practical example of a nonlinear system, an inverted pendulum will be controlled by a minimal set of rules to illustrate the performance and applicability of the proposed method.

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Authors and Affiliations

  1. Faculty of Information Science and Technology, Multimedia University, Malacca, Malaysia, 75450

    Aarthi Chandramohan

  2. Faculty of Engineering and Technology, Multimedia University, Malacca, Malaysia, 75450

    M. V. C. Rao

Authors
  1. Aarthi Chandramohan
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  2. M. V. C. Rao
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Correspondence to Aarthi Chandramohan.

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Chandramohan, A., Rao, M.V.C. A Novel Approach for Combining Fuzzy Rules Using Mean Operators for Effective Rule Reduction. Soft Comput 10, 1103–1108 (2006). https://doi.org/10.1007/s00500-006-0047-9

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  • DOI: https://doi.org/10.1007/s00500-006-0047-9

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