Showing papers in "Fuzzy Sets and Systems in 2008"

TL;DR: In this article, a multi-objective possibilistic mixed integer linear programming model (MOPMILP) is proposed for integrating procurement, production and distribution planning considering various conflicting objectives simultaneously as well as the imprecise nature of some critical parameters such as market demands, cost/time coefficients and capacity levels.

TL;DR: The purpose of this paper is to extend the TOPSIS method based on interval-valued fuzzy sets in decision analysis by providing a second-order regression model to highlight the effects of the numbers of alternatives, the number of attributes, and distance measures on average Spearmen correlation coefficients.

TL;DR: The necessity of applying a preprocessing step to deal with the problem of imbalanced data-sets is analyzed and the granularity of the fuzzy partitions, the use of distinct conjunction operators, the application of some approaches to compute the rule weights and theUse of different fuzzy reasoning methods are analyzed.

TL;DR: In order to clearly discriminate the different roles of fuzzy sets, input variables, and other components in achieving an interpretable fuzzy model, a taxonomy of fuzzy model interpretability is first proposed in terms of low- level interpretability and high-level interpretability in this paper.

TL;DR: An ontology of spatial relations is proposed, in order to guide image interpretation and the recognition of the structures it contains using structural information on the spatial arrangement of these structures.

TL;DR: Based on the basic concepts of ANNs and fuzzy regression models, a new hybrid method is proposed that yields more accurate results with incomplete data sets and the empirical results of financial market forecasting indicate that the proposed model can be an effective way of improving forecasting accuracy.

TL;DR: It is shown under some suitable conditions that an approximately additive function can be approximated by an additive mapping in a fuzzy sense.

TL;DR: A special emphasis is placed on advanced issues for improving accuracy and robustness, including a thorough comparison between global and local learning of consequent functions, a novel approach for detecting of and reacting on drifts in the data streams and an enhanced outlier treatment strategy.

TL;DR: An application to the analysis of time-series data on daily quotations of an investment fund over an eight year period is shown, some interesting linguistic summaries obtained, and results for different t-norms are presented.

TL;DR: This paper is concerned with the problem of adaptive fuzzy output tracking for a class of perturbed strict-feedback nonlinear systems with time delays and unknown virtual control coefficients, and the adaptive fuzzy tracking controller is designed by using the backstepping technique and Lyapunov-Krasovskii functionals.

TL;DR: This paper focuses on the construction of a fuzzy adaptive output feedback control based on any observer (high-gain (HG) observer, sliding mode (like) observer), for a class of single-input-single-output (SISO) uncertain or ill-defined affine nonlinear systems.

TL;DR: A special technique for reliability assessment of multi-state MSSs where performance rates or/and corresponding state probabilities are presented as fuzzy values is developed.

TL;DR: A generalized Hyers-Ulam-Rassias stability theorem in the fuzzy sense is established and it is proved that if a fuzzy approximate Jensen mapping is continuous at a point, then it can approximate it by an everywhere continuous Jensen mapping.

TL;DR: The problem of how to derive linguistic weights used in type-1 OWA aggregation given such type of quantifier is solved and type-2 linguistic quantifiers are proposed.

TL;DR: This paper proposes a hybridization of intelligent techniques such as ANNs, fuzzy systems and evolutionary algorithms, so that the final hybrid ARIMA-ANN model could outperform the prediction accuracy of those models when used separately.

TL;DR: A Banach contraction theorem in M-complete non-Archimedean fuzzy metric spaces (under arbitrary t-norms) is proved and partially answering a question of Gregori and Sapena.

TL;DR: A logical theory of the, so-called, trichotomous evaluative linguistic expressions (TEv-expressions) is presented and it is proved that essential properties of the vagueness phenomenon can be captured within the theory.

TL;DR: A critical introduction to neutrosophic logics is presented, focusing on the problem of defining suitable neutrosphic propositional connectives and discussing the relationship between neutrosophile logics and other well-known frameworks for reasoning with uncertainty and vagueness, such as (intuitionistic and interval-valued) fuzzy systems and Belnap's logic.

TL;DR: Many new results concerning fuzzy negations and (S,N)-implications, notably their characterizations with respect to the identity principle and ordering property, are presented, which give rise to some representation results.

TL;DR: This study develops a comprehensive optimization scheme and discusses its two-phase character in which the communication phase of the granular findings intertwines with the local optimization being realized at the level of the individual site and exploits the evidence collected from other sites.

TL;DR: This paper aims to develop simplified yet improved delay-dependent robust control for uncertain T-S fuzzy systems with time-varying delay through constructing new Lyapunov-Krasovskii functionals and improving Jensen's inequality.

TL;DR: The problem to find the nearest trapezoidal approximation of a fuzzy number with respect to a well-known metric, which preserves the expected interval of the fuzzy number, is completely solved.

TL;DR: The distributivity equation was investigated in families of certain operations (e.g. triangular norms, conorms, uninorms and nullnorms) and it was found that if the authors omit commutativity assumption, consideration of the left and right distributivity conditions is reasonable.

TL;DR: A family of copulas, called semilinear, is constructed starting with some assumptions about the linearity of the copulas along some segments of the unit square, and a special form of ordinal sum construction is introduced.

TL;DR: A sufficient and necessary condition, for discriminating whether a given solution is minimal or not, is shown and a new algorithm for computing all minimal solutions less than or equal to a given one is proposed.

TL;DR: Fuzzy number approximation by trapezoidal fuzzy numbers which preserves the expected interval is discussed and an adequate approximation operator might be chosen through the comparisons of some characteristics of the fuzzy number, like its ambiguity, width, its value and weighted expected value.

TL;DR: By decomposing a preference relation into a strict preference, an indifference, and an incomparability relation, this approach allows one to quantify different types of uncertainty in classification and thereby supports sophisticated classification and postprocessing strategies.

TL;DR: A property on binary operations, which is called @a-migrativity, is considered, and it is used to obtain t-norms by means of convex combinations of two t- norms, one of them being discontinuous.

TL;DR: The role played until now by these main soft computing ingredients is analyzed, and then an original proposal of the new constituents, mainly focused on the introduction of the broader topic of metaheuristics instead of evolutionary algorithms, is justified, presented and described.

TL;DR: This paper presents a direct self-structuring adaptive fuzzy control (DSAFC) scheme for affine nonlinear single-input-single-output systems and shows that the only restriction on the control gain is that it be positive.