In this paper we propose a random set framework for learning linguistic models for prediction problems. We show how we can model prediction problems based on learning linguistic p...
A granular based semantics for fuzzy measures is introduced in which the measure of a set of propositions approximates the probability of the disjunction of these propositions. Th...
A hybrid learning neuro-fuzzy system with asymmetric fuzzy sets (HLNFS-A) is proposed in this paper. The learning methods of random optimization (RO) and least square estimation (...
Abstract-- In this paper a new method for training singlemodel and multi-model fuzzy classifiers incrementally and adaptively is proposed, which is called FLEXFIS-Class. The evolvi...
In recent years, fuzzy logic has been applied successfully to a wide range of problems. This paper shows how it can be utilized in the area of spatial reasoning, in particular geo...