Propagating possibilistic and probabilistic variables through a mapping yields a fuzzy random variable. We propose a method to attach probability intervals to events pertaining to the output variable. We show that this method is consistent with classical approaches to fuzzy random variables and that the obtained probability interval is the mean value of the fuzzy probability defined by viewing ...

Upper and lower regression models (dual possibilistic models) are proposed for data analysis with crisp inputs and interval or fuzzy outputs. Based on the given data, the dual possibilistic models can be derived from upper and lower directions, respectively, where the inclusion relationship between these two models holds. Thus, the inherent uncertainty existing in the given phenomenon can be ap...

Recently, Carlsson and Fuller [C. Carlsson, R. Fuller, On possibilistic mean value and variance of fuzzy numbers, Fuzzy Sets and Systems 122 (2001) 315–326] have introduced possibilistic mean, variance and covariance of fuzzy numbers and Fuller and Majlender [R. Fuller, P. Majlender, On weighted possibilistic mean and variance of fuzzy numbers, Fuzzy Sets and Systems 136 (2003) 363–374] have in...

We have already formalized several models of the possibilistic linear regression analysis, where it is assumed that possibilistic parameters are non-interactive, i.e., the joint possibilistic distribution of parameters is defined by minimum operators. In this paper, we will deal with the interactive case in which quadratic membership functions defined by A. Celmins are considered. With the same...

today, transportation of hazardous materials (i.e., hazmat) is a very important issue for researchersdue to the risk of this transit, which should be considered for development of industries and transportation.therefore, a model that is useful should consider the risk and damage to humanitarianand environmental issues due to transit of hazmat materials. by considering the related cost, thereali...

Up to now, several algorithms for clustering large data sets have been presented. Most clustering approaches for data sets are the crisp ones, which cannot be well suitable to the fuzzy case. In this paper, the authors explore a single pass approach to fuzzy possibilistic clustering over large data set. The basic idea of the proposed approach (weighted fuzzy-possibilistic c-means, WFPCM) is to ...

This paper is a first step in the direction of extending possibilistic planning to take advantage of the expressive power and reasoning capabilities of fuzzy description logics. Fuzzy description logics are used to describe knowledge about the world and about actions. Fundamental definitions are given and the possibilistic planning problem is recast in this new setting.

This article proposes a novel approach to ranking fuzzy numbers based on WLUPM ( weighted lower and upper possibilistic means ). At first, by using this significance, we will compose WIVPM ( weighted intervalvalue possibilistic mean ), that this interval can be used as a crisp set approximation with respect to a fuzzy quantity. Therefore, with that, we define a method for ordering. This method ...

In 2001 Carlsson and Fullér introduced the possibilistic mean value, variance and covariance of fuzzy numbers. In 2002 Fullér and Majlender introduced the notations of crisp weighted possibilistic mean value, variance and covariance of fuzzy numbers, which are consistent with the extension principle. In this paper we will show some (normative) properties of possibility distributions.