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Evaluation of fully fuzzy regression models by fuzzy neural network

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Abstract

In this paper, a novel hybrid method based on fuzzy neural network for approximate fuzzy coefficients (parameters) of fuzzy linear and nonlinear regression models with fuzzy output and fuzzy inputs, is presented. Here, a neural network is considered as a part of a large field called neural computing or soft computing. Moreover, in order to find the approximate parameters, a simple algorithm from the cost function of the fuzzy neural network is proposed. Finally, we illustrate our approach by some numerical examples.

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Acknowledgments

The authors would like to thank the referees for valuable suggestions.

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Authors and Affiliations

  1. Department of Mathematics, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran

    M. Mosleh & M. Otadi

  2. Department of Mathematics, Science and Research Brench, Islamic Azad University, Tehran, 14778, Iran

    T. Allahviranloo

Authors
  1. M. Mosleh
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  2. T. Allahviranloo
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  3. M. Otadi
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Correspondence to T. Allahviranloo.

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Mosleh, M., Allahviranloo, T. & Otadi, M. Evaluation of fully fuzzy regression models by fuzzy neural network. Neural Comput & Applic 21 (Suppl 1), 105–112 (2012). https://doi.org/10.1007/s00521-011-0698-z

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  • DOI: https://doi.org/10.1007/s00521-011-0698-z

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