Probabilistic foundations for measurement modelling with fuzzy random variables
type: Item
instance of: scholarly article
title: Probabilistic foundations for measurement modelling with fuzzy random variables
zbMATH Open document ID: 1120.60032
author: Pedro Terán
published in: Fuzzy Sets and Systems
publication date: 2007-05-04T00:00:00Z
review text: Fuzzy random variables are a well justified concept to deal with randomness and fuzziness simultaneously. Within this concept, however, modelling of fuzziness is restricted to the use of minimum t-norm which implies that fuzziness persists through propagation. In this context, the present paper is the first serious attempt to use and to discuss other, especially Archimedean t-norms. The author discusses strong laws of large numbers and central limit theorems (CLT) for special types of fuzzy random variables and presents examples where the CLT do not hold.
reviewed by: Wolfgang Näther
Mathematics Subject Classification ID: 60F99
Mathematics Subject Classification ID: 26E50
zbMATH DE Number: 5149451
zbMATH Keywords: Archimedean t-norm
zbMATH Keywords: fuzzy random variable
zbMATH Keywords: central limit theorem
zbMATH Keywords: strong law of large numbers
MaRDI profile type: Publication
full work available at URL: j.fss.2006.12.006
OpenAlex ID: W2072604118
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DOI: 10.1016/J.FSS.2006.12.006
description: scientific article; zbMATH DE number 5149451