This paper exploits the ability of Symbiotic Evolution (SE), as a generic methodology, to elicit a fuzzy rule-base of the Mamdani-type. Almost all fuzzy rule-base generation algorithms produce rule-bases with redundant and overlapped membership functions that limit their interpretability elegance in their application. We address this problem by applying an algorithm to merge any similar members...

The present study considers a fuzzy natural color system (NCS) in which triangular pyramid membership functions are constructed on the NCS color triangle. This system can process a fuzzy input to an NCS and output a center of gravity of three weights associated with respective grades. Triangular membership functions are applied to the hue angle, and triangular pyramid membership functions are a...

In multi-objective evolutionary fuzzy systems, the process of tuning the membership functions plays an important role towards optimizing the systems accuracy. Although, the shape and position of the membership functions in the partition should not change too much with relation to the original partition, so that it does not lose its integrity. This paper presents and discusses multi-objective ev...

7 The generation of membership functions for fuzzy systems is a challenging problem. We show that for Mamdani-type fuzzy systems with correlation-product inference, centroid defuzzi cation, and triangular membership functions, optimizing 9 the membership functions can be viewed as an identi cation problem for a nonlinear dynamic system. This identi cation problem can be solved with an extended ...

A new technique for adaptation of fuzzy membership functions in a fuzzy inference system is proposed. The pointer technique relies upon the isolation of the specific membership functions that contributed to the final decision, followed by the updating of these functions’ parameters using steepest descent. The error measure used is thus backpropagated from output to input, through the min and ma...

Pattern recognition methods can be divided into four di erent categories: statistical or probabilistic, structural, possibilistic or fuzzy, and neural methods. A formal analysis shows that there is a computational complexity versus representational power trade-o between probabilistic and possibilistic or fuzzy set measures, in general. Furthermore, sigmoidal theory shows that fuzzy set membersh...

This paper gives the structure optimization of fuzzy control systems based on genetic algorithm in the MATLAB environment. The genetic algorithm is a powerful tool for structure optimization of the fuzzy controllers, therefore, in this paper, integration and synthesis of fuzzy logic and genetic algorithm has been proposed. The genetic algorithms are applied for fuzzy rules set, scaling factors ...

The generation of membership functions for fuzzy systems is a challenging problem. We show that for Mamdani-type fuzzy systems with correlation-product inference, centroid defuzzi%cation, and triangular membership functions, optimizing the membership functions can be viewed as an identi%cation problem for a nonlinear dynamic system. This identi%cation problem can be solved with an extended Kalm...

This paper presents priority based fuzzy goal programming approach to multi-objective quadratic programming problem. In the proposed approach, we construct the quadratic membership functions by determining the individual best solution of the objective functions subject to the system constraints. The quadratic membership functions are then transformed into equivalent linear membership functions ...