22 pages, accepté Reliable ComputingA number of techniques have been introduced to construct fuzzy models from measured data. One of the most common is the use of mathematical parametric models. In this paper, a new approach based on interval analysis is proposed to compute guaranteed estimates of suitable characteristics of the set of all values of the fuzzy parameter vector such that the error between experimental data and the model outputs belongs to some predefined feasible set. Subpavings consisting of boxes with nonzero width are used to encompass all the acceptable values of the parameter vector. The problem of estimating the parameters of the model is viewed as one of set inversion, which is solved in an approximate but guaranteed w...
In many applications, we know the function f(x1,...,xn), we know the intervals [xi] of possible valu...
Due to measurement uncertainty, often, instead of the actual values xi of the measured quantities, w...
This book develops a set of reference methods capable of modeling uncertainties existing in membersh...
22 pages, accepté Reliable ComputingA number of techniques have been introduced to construct fuzzy m...
Abstract—In this paper, we present a new method of interval fuzzy model identification. The method c...
Athenes, May 12-16Usually, fuzzy systems approximate functions by covering their graphs with fuzzy p...
Abstract—This correspondence addresses the problem of interval fuzzy model identification and its us...
International audienceThis chapter is an overview of past and present works dealing with fuzzy inter...
Abstract—A novel approach is introduced to construct a fuzzy regression model when both input data a...
In data processing, we often encounter the following problem: Suppose that we have processed the mea...
Using a set of confidence intervals, we develop a common approach, to construct a fuzzy set as an es...
ABSTRACT In data processing, we often encounter the following problem: Suppose that we have processe...
International audienceThis study deals with the derivation of a probabilistic parametric model from ...
[[abstract]]The method for obtaining the fuzzy estimates of regression parameters with the help of &...
Recently, there has been much research into effective representation and analysis of uncertainty in ...
In many applications, we know the function f(x1,...,xn), we know the intervals [xi] of possible valu...
Due to measurement uncertainty, often, instead of the actual values xi of the measured quantities, w...
This book develops a set of reference methods capable of modeling uncertainties existing in membersh...
22 pages, accepté Reliable ComputingA number of techniques have been introduced to construct fuzzy m...
Abstract—In this paper, we present a new method of interval fuzzy model identification. The method c...
Athenes, May 12-16Usually, fuzzy systems approximate functions by covering their graphs with fuzzy p...
Abstract—This correspondence addresses the problem of interval fuzzy model identification and its us...
International audienceThis chapter is an overview of past and present works dealing with fuzzy inter...
Abstract—A novel approach is introduced to construct a fuzzy regression model when both input data a...
In data processing, we often encounter the following problem: Suppose that we have processed the mea...
Using a set of confidence intervals, we develop a common approach, to construct a fuzzy set as an es...
ABSTRACT In data processing, we often encounter the following problem: Suppose that we have processe...
International audienceThis study deals with the derivation of a probabilistic parametric model from ...
[[abstract]]The method for obtaining the fuzzy estimates of regression parameters with the help of &...
Recently, there has been much research into effective representation and analysis of uncertainty in ...
In many applications, we know the function f(x1,...,xn), we know the intervals [xi] of possible valu...
Due to measurement uncertainty, often, instead of the actual values xi of the measured quantities, w...
This book develops a set of reference methods capable of modeling uncertainties existing in membersh...