This paper discusses a general approach to qualitative modeling based on fuzzy logic. The method of qualitative modeling is divided into two parts: fuzzy modeling and linguistic approximation. It proposes to use a fuzzy clustering method (fuzzy c-means method) to identify the structure of a fuzzy model. To clarify the advantages of the proposed method, it also shows some examples of modeling, a...

multi attribute decision making methods are considered as one of the most useful methods for solving ranking problems. in some decision making problems, while the alternatives for corresponding criteria are compared in a pairwise comparison manner, if the criteria are inherently fuzzy, debates will arise in ranking alternatives due to the closeness of the values of the criteria. in this researc...

This paper describes a method for formal compression of fuzzy systems. This method compresses a fuzzy system with an arbitrarily large number of rules into a smaller fuzzy system by removing the redundancy in the fuzzy rule base. As a result of this compression, the number of on-line operations during the fuzzy inference process is significantly reduced without compromising the solution. This r...

the present article investigates the application of high order tsk (takagi sugeno kang) fuzzy systems in modeling photo voltaic (pv) cell characteristics. a method has been introduced for training second order tsk fuzzy systems using anfis (artificial neural fuzzy inference system) training method. it is clear that higher order tsk fuzzy systems are more precise approximators while they cover n...

although many methods exist for intensity modulated radiotherapy (imrt) fluence map optimization for crisp data, based on clinical practice, some of the involved parameters are fuzzy. in this paper, the best fluence maps for an imrt procedure were identifed as a solution of an optimization problem with a quadratic objective function, where the prescribed target dose vector was fuzzy. first, a d...

in this article we consider the averaging method for differential inclusions with fuzzy right-hand side for the case when the limit of a method of an average does not exist.

This paper proposes a rule selection method with the destructive learning algorithm to construct a compact fuzzy classification system with high performance. In this paper, first we construct a fuzzy classification system by generating fuzzy rules from numerical data, and consider the fuzzy classification system based on fuzzy rules a network. Then we select significant fuzzy rules from the rul...

different methods have been proposed for finding the non-negative solution of fully fuzzy linear system (ffls) i.e. fuzzy linear system with fuzzy coefficients involving fuzzy variables. to the best of our knowledge, there is no method in the literature for finding the non-negative solution of a ffls without any restriction on the coefficient matrix. in this paper a new computational method is ...