In this paper we consider a constrained optimization problem where the objectives are fuzzy functions (fuzzy-valued functions). Fuzzy constrained Optimization (FO) problem plays an important role in many fields, including mathematics, engineering, statistics and so on. In the other side, in the real situations, it is important to know how may obtain its numerical solution of a given interesting...

In a great deal of literature on fuzzy regression analysis, most of research has focused on some predefined parametric forms of fuzzy regression relationships, especially on the fuzzy linear regression models. In many practical situations, it may be unrealistic to predetermine a fuzzy parametric regression relationship. In this paper, a fuzzy nonparametric model with crisp input and LR fuzzy ou...

In this paper, we have presented a new multivariate fuzzy time series forecasting method. This method assumes mfactors with one main factor of interest. History of past three years is used for making new forecasts. This new method is applied in forecasting total number of car accidents in Belgium using four secondary factors. We also make comparison of our proposed method with existing methods ...

This paper presents two new types of fuzzy shortest-path network problems. We consider the edge weight of the network as uncertain, which means that it is either imprecise or unknown. Thus, the first type of fuzzy shortest-path problem uses triangular fuzzy numbers for the imprecise problem. The second type uses level (1 − β, 1 − α) interval-valued fuzzy numbers, which are based on past statist...

Additive fuzzy systems can filter impulsive noise from signals. Alpha-stable statistics model the impulsiveness as a parametrized family of probability density functions or unit-area bell curves. The bell-curve parameter ct ranges through the interval (0, 2] and gives the Gaussian bell curve when 0t = 2 and gives the Cauchy bell curve when ~t = 1. The impulsiveness grows as ~ falls and the bell...

Wind power point forecasting is the primary method to deal with its uncertainty. However, in many applications, the probabilistic interval of wind power is more useful than traditional point forecasting. Methods to determine the probabilistic interval of wind power point forecasting value is very essential to power system operations. Based on the bootstrap method, this paper proposed a wavelet ...

Regression analysis is an area of statistics that deals with the investigation of the dependence of a variable upon one or more variables. Recently, much research has studied fuzzy estimation. There are some approaches existing in the literature for the estimation of the fuzzy regression model. Two of them are frequently used in parameter estimation, one of which is proposed by Tanaka et al [21...

This paper analyzes the performance of some fuzzy implications proposed in the bibliography together with the operators needed for their definition and for the fuzzy inference process, Examining the specialized literature, it is clear that the selection of the best fuzzy implication operator has become one of the main question in the design of a fuzzy system, being occasionally contradictory (a...