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On Possibilistic Dependencies: A Short Survey of Recent Developments

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Soft Computing Based Optimization and Decision Models

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 360))

Abstract

Carlsson and Fullér introduced the notions of possibilistic mean value and variance of fuzzy numbers. Fullér and Majlender introduced a measure of possibilistic covariance between marginal distributions of a joint possibility distribution as the average value of the interactivity relation between the level sets of its marginal distributions. Fullér et al. introduced the possibilistic correlation ratio, the possibilistic correlation coefficient and the possibilistic informational coefficient of correlation. In this paper we give a short survey of some later works which extend and develop these notions.

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Authors and Affiliations

  1. Department of Informatics, Széchenyi István University, Győr, Hungary

    Robert Fullér

  2. Department of Mathematics and Computational Sciences, Széchenyi István University, Győr, Hungary

    István Á. Harmati

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  1. Robert Fullér
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  2. István Á. Harmati
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Correspondence to Robert Fullér .

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Editors and Affiliations

  1. Department of Computer Science and A.I. Higher Technical School of Information Technology and Telecommunications Engineering, University of Granada, Granada, Spain

    David A. Pelta

  2. Department of Computer Science and A.I. Higher Technical School of Information Technology and Telecommunications Engineering, University of Granada , Granada, Spain

    Carlos Cruz Corona

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Fullér, R., Harmati, I.Á. (2018). On Possibilistic Dependencies: A Short Survey of Recent Developments. In: Pelta, D., Cruz Corona, C. (eds) Soft Computing Based Optimization and Decision Models. Studies in Fuzziness and Soft Computing, vol 360. Springer, Cham. https://doi.org/10.1007/978-3-319-64286-4_16

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