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Two New and Useful Defuzzification Methods Based on Root Mean Square Value

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Abstract

This paper presents two novel and useful defuzzification methods for fuzzy set outputs. Two algorithms based on root mean square (RMS) to obtain a new defuzzification procedure are proposed. In order to validate the efficacy of the proposed algorithms the results are compared with the existing defuzzification methods such as weighted average, centroid (COG) and mean of maxima. The satisfaction of a set of essential constraints is also dealt with which motivates a step towards rational defuzzification algorithm. These new methods RMS1and RMS2 stand on par with the most commonly used COG method in every respect. In addition, the value obtained by RMS2 is always higher and hence when a higher value is needed or desirable this can be employed advantageously.

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Authors and Affiliations

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

    Aarthi Chandramohan

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

    M. V. C. Rao & M. Senthil. Arumugam

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  1. Aarthi Chandramohan
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  2. M. V. C. Rao
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  3. M. Senthil. Arumugam
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Correspondence to Aarthi Chandramohan.

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Chandramohan, A., Rao, M.V.C. & Arumugam, M.S. Two New and Useful Defuzzification Methods Based on Root Mean Square Value. Soft Comput 10, 1047–1059 (2006). https://doi.org/10.1007/s00500-005-0042-6

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  • DOI: https://doi.org/10.1007/s00500-005-0042-6

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