ct 9 Words mean different things to different people, and so are uncertain. We, therefore, need a fuzzy set model for a word 10 that has the potential to capture their uncertaint...
Fuzziness (entropy) is a commonly used measure of uncertainty for type-1 fuzzy sets. For interval type-2 fuzzy sets (IT2 FSs), centroid, cardinality, fuzziness, variance and skewn...
In this paper we present a multi-scale method based on the hybrid notion of rough fuzzy sets, coming from the combination of two models of uncertainty like vagueness by handling r...
The two most important models of inferencing in approximate reasoning with fuzzy sets are Zadeh's Compositional Rule of Inference (CRI) and Similarity Based Reasoning (SBR). ...
For the last decades, research studies have been developed in which a coalition of Fuzzy Sets Theory and Statistics has been established with different purposes. These namely are:...
It is not an easy task to know a priori the most appropriate fuzzy sets that cover the domains of quantitative attributes for fuzzy association rules mining. In general, it is unre...
— Agents are being recommended as a next generation model for revising and restructuring the complex distributed applications. So the task of engineering quality for agent system...
In this paper, we discuss a formalism for modeling regions that are exposed to movement or deformation. The basis of our formalism is the RCC theory, which uses topological relati...
Images of fuzzy relations provide powerful access to fuzzifications of properties of and/or relationships between fuzzy sets. As an important example, images of fuzzy orderings c...