Fuzzy to Random Uncertainty Alignment
Abstract
The objective of this paper is to present new and simple mathematical approach to deal with uncertainty alignment between fuzzy and random data. In particular we present a method to describe fuzzy (possibilistic) distribution in terms of a pair (or more) of related random (probabilistic) events, both fixed and variable. Our approach uses basic properties of both fuzzy and random distributions. We show that the data fuzziness can be viewed as a non uniqueness of related random events. We also show how fuzzy-random consistancy principle can be given precise mathemtaical meaning. Various types of fuzzy distributions are examined, special cases considered, and several numerical examples presented.
Keywords
Fuzzy distributions;Cumulative random distributions;Probability of random events;Fuzzy to random uncertainty alignment;Unimodal and multimodal fuzzy data;Consistency principle
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PDFDOI: http://dx.doi.org/10.21533/scjournal.v5i1.108
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Copyright (c) 2016 Migdat Hodzic
ISSN 2233 -1859
Digital Object Identifier DOI: 10.21533/scjournal
This work is licensed under a Creative Commons Attribution 4.0 International License