To apply fuzzy logic, two major tasks need to be performed: the derivation of production rules and the determination of membership functions. These tasks are often difficult and time consuming. This paper presents an algorithmic method for generating membership functions and fuzzy production rules; the method includes an entropy minimization for screening analog values. Membership functions are...

Enhanced fuzzy modeling by multivariable fuzzy membership functions is described. From the interpretability issues viewpoint conventionally fuzzy modeling is carried out by means of decomposition of multivariable membership functions via projections on each variable component. However, due to decomposition there involves an error while reconstructing the model output from the contributions of e...

Determination of the fuzzy membership functions in a given fuzzy logic system is the key factor for resulting in the best performance. Thus, in this study, particle swarm optimization (PSO) and artificial bee colony (ABC), relatively new member of swarm intelligence, are used to adjust the shape of fuzzy membership functions, respectively. Proposed methods have been implemented and compared for...

In this paper, we propose a neuro-fuzzy inference circuit that generates membership functions and inference rules automatically in the learning process. In this circuit, we use membership functions which are generated by only using NOT operations and bit shift operations and tune only the parameters of the consequent part to reduce the circuit scale. In spite of those limitations, this circuit ...

This paper proposes a fuzzy goal programming based on Taylor series for solving decentralized bilevel multiobjective fractional programming (DBLMOFP) problem. In the proposed approach, all of the membership functions are associated with the fuzzy goals of each objective at the both levels and also the fractional membership functions are converted to linear functions using the Taylor series appr...

In this paper, we propose fuzzy linear programming support vector machines (LP-SVMs) that resolve unclassifiable regions for multiclass problems. Namely, in the directions orthogonal to the decision functions obtained by training the LP-SVM, we define membership functions. Then by the minimum or average operation for these membership functions we define a membership function for each class. We ...

An Enterprise resource Planning (ERP) system is packaged business software that integrates organizational process and functions into a unified system. Many researchers and practitioners agree that Enterprise Resource Planning (ERP) systems are the most important development in terms of corporate use of information technology (IT) in the 1990s. In this author predict a Comparative study of Anfis...

chaotic systems are nonlinear dynamic systems, the main feature of which is high sensitivity to initial conditions. to initiate a design process in fuzzy model, chaotic systems must first be represented by t-s fuzzy models. in this paper, a new fuzzy modeling method based on sector nonlinearity approach has been recommended for chaotic systems relating to initial condition variations using the ...

The fuzzy rule based inference is known to be a useful tool to capture the behavior of an approximate system in transportation. One of the obstacles of implementing the fuzzy rule based inference, however, has been to calibrate the membership functions of the fuzzy sets used in the rules. This paper proposes a way to calibrate the membership function when a set of input and output data is given...

This paper presents fuzzy goal programming approach for solving multiobjective quadratic programming problem. The problem deals with a decisionmaking unit with multiple objective functions, which are quadratic in nature and the system constraints are linear functions. In the proposed approach, we first formulate the quadratic membership functions by determining best solution of the objective fu...