This paper presents a study on inference in a Fuzzy Logic Controller (FLC). Inference is made up of interpretation, implication, combination and defuzzification. These last two steps can be performed in two sequences. An explanation, through approximate reasoning, on how to implement other than the welìknown Mamdani and Larsen implications is given. (Dis)advantages of several combinations of im...

Fuzzy time series approaches, which do not require the strict assumptions of traditional time series approaches, generally consist of three stages. These stages are called as the fuzzification of crisp time series observations, the identification of fuzzy relationships and the defuzzification, respectively. All of these stages play an important role on the forecasting performance of the model. ...

This paper presents a new learning algorithm for the design of Mamdani-type or fully-linguistic fuzzy controllers based on available input-output data. It relies on the use of a previously introduced parametrized defuzzification strategy. The learning scheme is supported by an investigated property of the defuzzification method. In addition, the algorithm is tested by considering a typical non-...

The goal of this paper is to solve a matrix game with fuzzy payoffs. In this paper, a fuzzy matrix game has been considered and its solution methodology has been proposed. In this paper, fuzzy payoff values are assumed to be trapezoidal fuzzy numbers. Then the corresponding matrix game has been converted into crisp game using defuzzification of fuzzy number. Here, widely known signed distance m...

Many applications of fuzzy set theory require defuzzification and ranking approaches based on alpha level sets because exact membership functions may not always be available. In this article, we have assumed that exact membership functions can be approximated using piecewise linear functions based on alpha level sets and derived two analytical formulas to meet such a requirement. The two formul...

 Fuzzy C-Means (FCM) is an unsupervised clustering method that has been used extensively in data analysis and image segmentation. The defuzzification of the fuzzy partition of FCM is usually done using the maximum membership degree principle which may not be appropriate for some real-world applications. In this paper, we present a new algorithm that generates a probabilistic model of the fuzzy...

This paper presents a study on inference in a Fuzzy Logic Controller (FLC). Inference is made up of interpretation, implication, combination and defuzzification. These last two steps can be performed in two sequences. An explanation, through approximate reasoning, on how to implement other than the welìknown Mamdani and Larsen implications is given. (Dis)advantages of several combinations of im...

in this paper, we deal with fuzzy random variables for inputs andoutputs in data envelopment analysis (dea). these variables are considered as fuzzyrandom flat lr numbers with known distribution. the problem is to find a method forconverting the imprecise chance-constrained dea model into a crisp one. this can bedone by first, defuzzification of imprecise probability by constructing a suitablem...