Showing papers in "Fuzzy Sets and Systems in 2003"

TL;DR: The relationships between intuitionistic fuzzy sets are established and interval-valued fuzzy sets, an extension of fuzzy set theory, are established.

TL;DR: A new approach for deriving priorities from fuzzy pairwise comparison judgements is proposed, based on α-cuts decomposition of the fuzzy judgements into a series of interval comparisons, which requires the solution of a non-linear optimisation program.

TL;DR: This method combines tree growing and pruning, to determine the structure of the soft decision tree, with refitting and backfitting, to improve its generalization capabilities.

TL;DR: The approach transforms fuzzy DEA models into possibility DEA models by using possibility measures of fuzzy events (fuzzy constraints) and it is shown that for the special case, in which fuzzy membership functions of fuzzy data are of trapezoidal types, possibility DEA model become linear programming models.

TL;DR: The induced ordered weighted averaging (IOWA) operator is introduced and it is shown its possibilities in modeling nearest-neighbor rules and also used to establish a new class of information fusion models called "best yesterday models".

TL;DR: An overview of interval analysis, its development, and its relationship to fuzzy set theory is given.

TL;DR: A theorem similar to the one presented by Smets and Magrez is obtained, in which the strong negation c used is not generated by the same automorphism that generates the implication.

TL;DR: The notations of weighted interval-valued possibilistic mean value, variance and covariance of fuzzy numbers are introduced, which are consistent with the extension principle and it is shown that the weighted variance of linear combination of fuzzyNumbers can be computed in a similar manner as in probability theory.

TL;DR: This paper analytically derive the minimal variability weighting vector for any level of orness, using the Kuhn-Tucker second-order sufficiency conditions for optimality.

TL;DR: A (heuristic) real option rule in a fuzzy setting, where the present values of expected cash flows and expected costs are estimated by trapezoidal fuzzy numbers, is introduced and the optimal exercise time is determined by the help of possibilistic mean value and variance of fuzzy numbers.

TL;DR: Here the authors consider methodologies for constructing recommender systems that are based solely on the preferences of the single individual for whom they are providing the recommendation and make no use of the preference of other collaborators.

TL;DR: In this paper, the Choquet integral is defined as a possible aggregation operator that combines information concerning the preferences of the decision maker over each attribute and his preferences about aggregation of criteria (interacting criteria).

TL;DR: The method of variable change on the under- and over- deviational variables of the membership goals associated with the fuzzy goals of the model is introduced to solve the problem efficiently by using linear goal programming (LGP) methodology.

TL;DR: This work develops some fuzzy versions of the classical DEA models by using some ranking methods based on the comparison of α-cuts, and shows, in a numerical example, how these models become specially useful for detecting sensitive decision-making units.

TL;DR: The definition of a fuzzy subgroups with thresholds is given, which is a generalization of Rosenfeld's fuzzy subgroup and Bhakat and Das's fuzzy group and discusses relations between two fuzzy sub groups.

TL;DR: A fuzzy mining algorithm based on Srikant and Agrawal's method is proposed for extracting implicit generalized knowledge from transactions stored as quantitative values and integrates fuzzy-set concepts and generalized data mining technologies to achieve this purpose.

TL;DR: A new kind of mapping rule base scheme is proposed to get the fuzzy rules of hierarchical fuzzy systems such that one can easily design the involved fuzzy rules in the middle layers of the hierarchical structure.

TL;DR: The Lyapunov synthesis approach is used to develop a state-feedback adaptive control algorithm based on the adaptive fuzzy model and it is shown that, in the special case, the tracking error exponentially converges to zero even though the approximation errors exist.

TL;DR: Two original contributions are developed that can enhance the application of Fuzzy Rough Sets techniques to data that may be affected by several sources of uncertainty in its measurement process.

TL;DR: Some existence results for the impulsive functional differential inclusion and the fuzzy impulsivefunctional differential equation with some conditions are established and the properties of the solution set and the attainable set are studied.

TL;DR: This paper presents an intuitionistic fuzzy version of the triangular compositions of Bandler and Kohout and the variants of these compositions given by De Baets and Kerre, and investigates some properties ofThese compositions: containment, convertibility, monotonicity, interaction with union and intersection.

TL;DR: Using the basic idea underlying SVM for multivariate fuzzy linear and nonlinear regression models gives computational efficiency of getting solutions.

TL;DR: A multicriteria group decision making model based on fuzzy set theory is developed to improve the configuration items selection process and ranks candidate items into partial or complete orders that can assist decision makers in selecting more proper set of configuration items.

TL;DR: The convergence rate of SVIRNs is faster than the conventional networks with BP learning algorithms or with robust BPlearning algorithms for interval regression analysis, and a traditional back-propagation (BP) learning algorithm can be used to adjust the initial structure networks of SVirNs under training data sets without or with outliers.

TL;DR: A characterization theorem is stated that gives an improvement of a well-known theorem of Czogala and Drewniak on idempotent, associative and increasing operations with neutral element, as well as an improved of a characterization theorem for left (and right) continuous, idem Potent uninorms.

TL;DR: The aim in this paper is to discuss the difference between two different type of Cauchy sequences used in the literature to prove fixed point theorems in fuzzy metric spaces.

TL;DR: A new fuzzy control technique, which belongs to the popular family of control algorithms, called Model Predictive Controllers, which minimizes the difference between the model predictions and the desired trajectory over the prediction horizon and the control energy over a shorter control horizon.

TL;DR: The main aim of this paper is to complete the decision model studying conditions under which reciprocity property is maintained when aggregating preference relations using an OWA operator guided by a relative linguistic quantifier.

TL;DR: The new definition of the fuzzy norm of a linear operator from one fuzzy normed linear space into another is introduced; and the boundedness of such an operator is described, and the space of all bounded linear operators endowed with this fuzzy norm is studied.

TL;DR: A new e-insensitive Fuzzy C-Means (eFCM) clustering algorithm with insensitivity control named αFCM and βFCM is introduced and performance is experimentally compared with the FCM method using synthetic data with outliers and heavy-tailed and overlapped groups of data in background noise.