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How to Gauge the Accuracy of Fuzzy Control Recommendations: A Simple Idea

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Fuzzy Logic in Intelligent System Design (NAFIPS 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 648))

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Abstract

Fuzzy control is based on approximate expert information, so its recommendations are also approximate. However, the traditional fuzzy control algorithms do not tell us how accurate are these recommendations. In contrast, for the probabilistic uncertainty, there is a natural measure of accuracy: namely, the standard deviation. In this paper, we show how to extend this idea from the probabilistic to fuzzy uncertainty and thus, to come up with a reasonable way to gauge the accuracy of fuzzy control recommendations.

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Acknowledgments

This work was supported in part by NSF grant HRD-1242122.

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Authors and Affiliations

  1. Department of Computer Science, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Patricia Melin & Oscar Castillo

  2. University of Texas at El Paso, 500 W. University, El Paso, TX, 79968, USA

    Andrzej Pownuk, Olga Kosheleva & Vladik Kreinovich

Authors
  1. Patricia Melin
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  2. Oscar Castillo
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  3. Andrzej Pownuk
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  4. Olga Kosheleva
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  5. Vladik Kreinovich
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Corresponding author

Correspondence to Patricia Melin .

Editor information

Editors and Affiliations

  1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Patricia Melin

  2. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Oscar Castillo

  3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  4. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada

    Marek Reformat

  5. Laboratory of Computational Intelligence and Automation, University of Waterloo, Waterloo, Ontario, Canada

    William Melek

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Melin, P., Castillo, O., Pownuk, A., Kosheleva, O., Kreinovich, V. (2018). How to Gauge the Accuracy of Fuzzy Control Recommendations: A Simple Idea. In: Melin, P., Castillo, O., Kacprzyk, J., Reformat, M., Melek, W. (eds) Fuzzy Logic in Intelligent System Design. NAFIPS 2017. Advances in Intelligent Systems and Computing, vol 648. Springer, Cham. https://doi.org/10.1007/978-3-319-67137-6_32

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  • DOI: https://doi.org/10.1007/978-3-319-67137-6_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67136-9

  • Online ISBN: 978-3-319-67137-6

  • eBook Packages: EngineeringEngineering (R0)

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