This paper presents a general framework for the study of rough set approximation operators in fuzzy environment in which both constructive and axiomatic approaches are used. In constructive approach, a pair of lower and upper generalized fuzzy rough (and rough fuzzy, respectively) approximation operators is first defined. The representations of both fuzzy rough approximation operators and rough...

In this paper, computer vision and fuzzy set theory are merged for the robust construction of three-dimensional objects using a small number of cameras and minimal a priori knowledge about the objects. This work extends our previously defined crisp model, which has been successfully used for recognizing and linguistically summarizing human activity. The objects true features more closely resemb...

In this paper, a fuzzy quadratic minimum spanning tree problem is formulated as expected value model, chance-constrained programming and dependent-chance programming according to different decision criteria. Then the crisp equivalents are derived when the fuzzy costs are characterized by trapezoidal fuzzy numbers. Furthermore, a simulation-based genetic algorithm using Prüfer number representat...

In Fuzzy constraints satisfaction problem (FCSP), fuzzy constraints are aggregated by min operation into a fuzzy set membership function to be maximized. This representation framework, originally expressed in terms of membership functions, can be equivalently translated into a set of prioritized crisp constraints. We take advantage of this representation for modeling aggregations different from...

Fuzzy Description Logics (DLs) with t-norm semantics have been studied as a means for representing and reasoning with vague knowledge. Recent work has shown that even fairly inexpressive fuzzy DLs become undecidable for a wide variety of t-norms. We complement those results by providing a class of t-norms and an expressive fuzzy DL for which ontology consistency is linearly reducible to crisp r...

Crisp comparison matrices produce crisp weight estimates. It is logical for an interval or fuzzy comparison matrix to give an interval or fuzzy weight estimate. In this paper, an eigenvector method (EM) is proposed to generate interval or fuzzy weight estimate from an interval or fuzzy comparison matrix, which differs from Csutora and Buckley’s LambdaMax method in several aspects. First, the pr...

In the literature, there are a lot of methods concerning the problem of ordering the interval numbers k , ~ ] , [y,g], ... (', ') or the fuzzy ones A, B , ... (see 4, and for a n overview of methods). All of these methods can be classified a s belonging t o two different approaches. (i) Ordering t h e crisp or the fuzzy intervals using binary order relations: [ c , ~ ] 4 [ y , ~ ] , A 5 B, .......

in this paper, by using a new approach on distance between two fuzzy numbers, we construct a new ranking system for fuzzy number which is very realistic and also matching our intuition as the crisp ranking system on r.

Decision tree induction is one of common approaches for extracting knowledge from a sets of feature-based examples. In real world, many data occurred in a fuzzy and uncertain form. The decision tree must able to deal with such fuzzy data. This paper presents a tree construction procedure to build a fuzzy decision tree from a collection of fuzzy data by integrating fuzzy set theory and entropy. ...

Comparison and data analysis to the similarity measures and entropy for fuzzy sets are studied. The distance proportional value between the fuzzy set and the corresponding crisp set is represented as fuzzy entropy. We also verified that the sum of the similarity measure and the entropy between fuzzy set and the corresponding crisp set constitutes the total information. Finally, we derive a simi...