In [13], we proposed that there are three kinds of negative relations which contradictory negative relation, opposite negative relation and medium negative relation in fuzzy information, and that defined a new fuzzy set FSCOM with contradictory negation, opposite negation and medium negation. In order to show applicability of FSCOM, this paper apply FSCOM to fuzzy decision making in an actual e...

|Fuzzy Logic Controllers constitute knowledge-based systems that include fuzzy rules and fuzzy membership functions to incorporate the human knowledge into their knowledge base. The deenition of fuzzy rules and fuzzy membership functions is actually aaected by subjective decisions, having a great innuence over the whole FLC performance. Some eeorts have been made to obtain an improvement on sys...

defuzzifier circuit is one of the most important parts of fuzzy logic controllers that determine the output accuracy. the center of gravity method (cog) is one of the most accurate methods that so far been presented for defuzzification. in this paper, a simple algorithm is presented to generate triangular output membership functions in the mamdani method using the multiplier/divider circuit and...

An important issue in the design of FRBS is the formation of fuzzy if-then rules and the membership functions. This paper presents a Mixed Genetic Algorithm (MGA) approach to obtain the optimal rule set and the membership function of the fuzzy classifier. While applying genetic algorithm for fuzzy classifier design, the membership functions are represented as real numbers and the fuzzy rules ar...

Wang and Mendel proved (1991) that fuzzy systems with product inference, cen-troid defuzziication, and everywhere positive membership functions (in particular, Gaus-sians, Wang, 1992) are capable of approximating any real continuous control function on a compact set to arbitrary accuracy. Kosko (1992) proved that fuzzy systems, in which membership functions have compact support, and combination...

We examine the performance of a fuzzy genetics-based machine learning method for multidimensional pattern classification problems with continuous attributes. In our method, each fuzzy if-then rule is handled as an individual, and a fitness value is assigned to each rule. Thus, our method can be viewed as a classifier system. In this paper, we first describe fuzzy if-then rules and fuzzy reasoni...

This paper describes a novel nonlinear modeling approach by on-line clustering, fuzzy rules and support vector machine. Structure identification is realized by an on-line clustering method and fuzzy support vector machines, the fuzzy rules are generated automatically. Time-varying learning rates are applied for updating the membership functions of the fuzzy rules. Finally, the upper bounds of t...

Reactive power plays an important role in supporting real power transmission, maintaining system voltages within proper limits and overall system reliability. In this paper, the production cost of reactive power, cost of the system transmission loss, investment cost of capacitor banks and absolute value of total voltage deviation (TVD) are included into the objective function of the power flow ...

In this paper we are dealing with the construction of a fuzzy rule based classifier. A three-step method is proposed based on Lukasiewicz logic for the description of the rules and the fuzzy memberships to construct concise and highly comprehensible fuzzy rules. In our method, a genetic algorithm is applied to evolve the structure of the rules and then a gradient based optimization to fine tune...

Predicting the wear performance of circular diamond saw in the process of sawing hard dimensional stone is an important step in reducing production costs in the stone sawing industry. In the present research work, the effective parameters on circular diamond saw wear are defined, and then the weight of each parameter is determined through adopting a fuzzy rock engineering system (Fuzzy RES) bas...