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Similarities and distances in fuzzy regression modeling

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Abstract

We study the set of the solutions of a fuzzy regression model as a metric space. For each metric, we define a similarity ratio in order to compare the spaces of solutions of a fuzzy regression model. We prove that the similarity ratios, that can be extracted from these different metrics, are all the same as in [4]. As an application, we use the similarity ratio to produce fuzzy classification of models. A numerical example, involving economic data, is given.

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Authors and Affiliations

  1. Democritus University of Thrace, Department of Civil Engineering, 671 00, Xanthi, Greece

    B. K. Papadopoulos

  2. University of Macedonia, Department of Applied Informatics, Alex. Michailidis str, 41 546 41, Thessaloniki Greece

    M. A. Sirpi

Authors
  1. B. K. Papadopoulos
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  2. M. A. Sirpi
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Correspondence to B. K. Papadopoulos.

Additional information

The research reported in this paper was carried out in the framework of MathInd Project

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Papadopoulos, B., Sirpi, M. Similarities and distances in fuzzy regression modeling. Soft Computing 8, 556–561 (2004). https://doi.org/10.1007/s00500-003-0314-y

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  • DOI: https://doi.org/10.1007/s00500-003-0314-y

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