Topological relations have played important roles in spatial query, analysis and reasoning in Geographic Information Systems (GIS) and spatial databases. The topological relations between crisp and fuzzy spatial objects based upon the 9intersections topological model have been identified. However the formalization of the topological relations between fuzzy regions needs more investigation. The ...

Uncertainty is an inherent property of all living systems. Curiously enough, computational models inspired by biological systems do not take, in general, under consideration this essential aspect of living systems. In this paper, after introducing the notion of a multi-fuzzy set (i.e. an orthogonal approach to the fuzzification of multisets), we introduce two variants of P systems with fuzzy co...

in previous studies we first concentrated on utilizing crisp simulationto produce discrete event fuzzy systems simulations. then we extendedthis research to the simulation of continuous fuzzy systems models. in this paperwe continue our study of continuous fuzzy systems using crisp continuoussimulation. consider a crisp continuous system whose evolution depends ondifferential equations. such a ...

expert systems are computer programs that make the knowledge of experts available when a human expert is not with in easy reach. the systems are to simulate the thinking and inference pattern of human being. the ultimate goal of expert system is to be analogous to human as much as possible. utilizing the intelligent system in commerce is indispensable for establishing a better connection with c...

in this study, a multi-objective genetic algorithm (moga) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear multi-input multi-output (mimo) systems. in the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. furthermore, se- curing low-level and high-level ...

The integration of neural networks and fuzzy inference systems could be formulated into three main categories: cooperative, concurrent and integrated neuro-fuzzy models. We present three different types of cooperative neuro-fuzzy models namely fuzzy associative memories, fuzzy rule extraction using self-organizing maps and systems capable of learning fuzzy set parameters. Different Mamdani and ...

in this study, we introduce and study a concept of distributed fuzzymodeling. fuzzy modeling encountered so far is predominantly of a centralizednature by being focused on the use of a single data set. in contrast to this style ofmodeling, the proposed paradigm of distributed and collaborative modeling isconcerned with distributed models which are constructed in a highly collaborativefashion. i...