From both a theoretical and a practical point of view, the study of the concept of independence has great importance in any formalism that manages uncertainty. In Independence Concepts in Possibility Theory: Part I (de Campos and Huete, Fuzzy Sets and Systems 103 (1999) 127-152) several independence relationships were proposed, using different comparison criteria between conditional possibility...

Type-2 (T2) fuzzy variable is an extension of an ordinary fuzzy variable. In fuzzy possibility theory, T2 fuzzy variable is defined as a measurable map from the universe to the set of real numbers, and the possibility of a T2 fuzzy variable takes on a real number is a regular fuzzy variable (RFV). T2 fuzziness, which is usually used to handle linguistic uncertainties, can be described as T2 fuz...

We develope a construction of an L-fuzzy valued measure by extending a measure defined on a σ-algebra of crisp sets to an L-fuzzy valued TM-countably additive measure defined on a TMclan of L-fuzzy sets in the case when operations for L-fuzzy sets and L-fuzzy real numbers are based on the minimum t-norm TM. Keywords— L-fuzzy set, L-fuzzy real number, L-fuzzy valued measure.

Allowing for flexible queries enables database users to express preferences inside minimal requirements, and, if necessary, priorities inside compound queries. In other words, clear-cut properties can be refined by ordering the interpretations compatible with them, according to user's preferences. Often the representation of these preferences can be viewed as modelling linguistic-like terms in ...

Uncertainty is a prominent feature of any major project. Yet, addressing this uncertainty and dealing with its impact is arguably one of the most remarkable topics of this period. Nevertheless, with the increased level of complexity and the emphasis on avoiding project cost overruns, there is an even higher emphasis on researchers to deliver an improved methodology for dealing with risk and unc...

Clustering is a standard approach in analysis of data and construction of separated similar groups. The most widely used robust soft clustering methods are fuzzy, rough and rough fuzzy clustering. The prominent feature of soft clustering leads to combine the rough and fuzzy sets. The Rough Fuzzy C-Means (RFCM) includes the lower and boundary estimation of rough sets, and fuzzy membership of fuz...

Inthispaper, (L,M)-fuzzy domain finiteness and (L,M)-fuzzy restricted hull spaces are introduced, and several characterizations of the category (L,M)-CS of (L,M)-fuzzy convex spaces are obtained. Then, (L,M)-fuzzy stratified (resp. weakly induced, induced) convex spaces are introduced. It is proved that both categories, the category (L,M)-SCS of (L,M)-fuzzy stratified convex spaces and the cate...

A discrete Sugeno integral on a bounded distributive lattice L is defined as an idempotent weighted polynomial. Another possibility for axiomatization of integrals to consider compatible aggregation functions, uniquely extending the L-valued fuzzy measures. This paper aims study mentioned unique extension property concerning possible non-distributive lattices. We show that this equivalent distr...

Coevolutionary algorithms have received increased attention in the past few years within the domain of evolutionary computation. In this paper we combine the search power of coevolutionary computation with the expressive power of fuzzy systems, presenting Fuzzy CoCo: Fuzzy Cooperative Coevolution. We demonstrate the efficacy of Fuzzy CoCo by applying it to two hard problems—plant classification...