When we face a problem with a high number of variables by a standard fuzzy system, the number of rules increases exponentially and then the obtained fuzzy system is scarcely interpretable. This problem can be handled by arranging the inputs in hierarchical ways. The paper presents a multi-objective Genetic Algorithm that learns Serial Hierarchical Fuzzy Systems with the aim of coping the curse ...

In this paper, we use both fuzzy optimization and normal simulation methods to solve fuzzy web planning model problems, which are queuing system problems for designing web servers. We apply fuzzy probabilities to the queuing system models with customers arrival rate λ and servers’ service rate μ, and then compute fuzzy system performance variables, including Utilization, Number (of requests) in...

Multi-fuzzy set theory is an extension of fuzzy set theory, L-fuzzy set theory and Atanassov intuitionistic fuzzy set theory. In this paper we study the relation between Atanassov intuitionistic fuzzy and the proposed extension called Multi-fuzzy. Also we present the notion of Multi-fuzzy mappings and Atanassov Intuitionistic Fuzzy Sets Generating Maps. Mathematics Subject Classification: MSC: ...

This paper proposes a fuzzy classifier system (FCS) using fuzzy rules given by hyper-cone membership functions. The hyper-cone membership function is expressed by a kind of radial basis function, and its fuzzy rules can be flexibly located in input and output spaces. Therefore, The FCS can generate excellent rules which have the best location and shape of membership functions. We apply the FCS ...

This paper develops and experimentally demonstrates a robust automatic parallel parking algorithm for parking in tight spaces. Novel fuzzy logic controllers are designed for each step of the maneuvering process. The controllers are first demonstrated by simulation using the kinematic model of a skid steering autonomous ground vehicle (AGV). They are then demonstrated experimentally on a skid st...

This paper presents the fuzzy expert system for intelligent support of decision making about cause of stone construction crack of building. The system is based on some linguistic expert expressions formalised by 9 fuzzy knowledge bases. Tuning of fuzzy rules by genetic algorithms provided a good concordance between real causes of cracks and results of decision making by the system.

Bio-inspired algorithms like Genetic Algorithms and Fuzzy Inference Systems (FIS) are nowadays widely adopted as hybrid techniques in commercial and industrial environment. In this paper we present an interesting application of the fuzzy-GA paradigm to Smart Grids. The main aim consists in performing decision making for power flow management tasks in the proposed microgrid model equipped by ren...

Abstract— In this paper, a new extended method of multi criteria decision making based on fuzzy-Topsis theory is introduced. fuzzy mcdm algorithm for determining the best choice among all possible choices when the data are fuzzy is also presented. Using a new index leads to procedure for choosing fuzzy ideal and negative ideal solutions directly from the fuzzy data observed alternatives.in this...

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 ...