Generating negations of probability distributions

Ildar Batyrshin, Luis Alfonso Villa-Vargas, Marco Antonio Ramírez-Salinas, Moisés Salinas-Rosales, Nailya Kubysheva

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

3 Citas (Scopus)

Resumen

Recently, the notation of a negation of a probability distribution was introduced. The need for such negation arises when a knowledge-based system can use the terms like NOT HIGH, where HIGH is represented by a probability distribution (pd). For example, HIGH PROFIT or HIGH PRICE can be considered. The application of this negation in Dempster–Shafer theory was considered in many works. Although several negations of probability distributions have been proposed, it was not clear how to construct other negations. In this paper, we consider negations of probability distributions as point-by-point transformations of pd using decreasing functions defined on [0,1] called negators. We propose the general method of generation of negators and corresponding negations of pd, and study their properties. We give a characterization of linear negators as a convex combination of Yager’s and uniform negators.

Idioma originalInglés
Páginas (desde-hasta)7929-7935
Número de páginas7
PublicaciónSoft Computing
Volumen25
N.º12
DOI
EstadoPublicada - jun 2021

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