In this paper, we propose a novel approach, based on entropy and similarity measure of intuitionistic fuzzy sets, to determine weights of the IFOWA operator. Then we define a new intuitionistic fuzzy dependent OWA (IFDOWA) operator which is applied to handling multi-attribute group decision making problem with intuitionistic fuzzy information. Finally, an example is given to demonstrate the rat...

in this paper, we use parametric form of fuzzy number, then aniterative approach for obtaining approximate solution for a classof nonlinear fuzzy fredholmintegro-differential equation of the second kindis proposed. this paper presents a method based on newton-cotesmethods with positive coefficient. then we obtain approximatesolution of the nonlinear fuzzy integro-differential equations by an it...

in this paper, a novel hybrid method based on learning algorithmof fuzzy neural network and newton-cotesmethods with positive coefficient for the solution of linear fredholm integro-differential equation of the second kindwith fuzzy initial value is presented. here neural network isconsidered as a part of large field called neural computing orsoft computing. we propose alearning algorithm from ...

One-third of the people with an age over twenty have some signs of degenerated discs. However, in most of the patients the mere presence of degenerative discs is not a problem leading to pain, neurological compression, or other symptoms. This paper presents an interval type-2 fuzzy hybrid rule-based system to diagnose the abnormal degenerated discs where pain variables are represented by interv...

today, stock investment has become an important mean of national finance. apparently, it is significant for investors to estimate the stock price and select the trading chance accurately in advance, which will bring high return to stockholders. in the past, long-term trading processes and many technical analysis methods for stock market were put forward. however, stock market is a nonlinear sys...

This paper deals with the problem of testing statisticalhypotheses when the available data are fuzzy. In this approach, wefirst obtain a fuzzy test statistic based on fuzzy data, and then,based on a new signed distance between fuzzy numbers, we introducea new decision rule to accept/reject the hypothesis of interest.The proposed approach is investigated for two cases: the casewithout nuisance p...

Ranking fuzzy numbers plays a main role in many applied models inreal world and in particular decision-making procedures. In manyproposed methods by other researchers may exist some shortcoming.The most commonly used approaches for ranking fuzzy numbers isbased on defuzzification method. Many ranking fuzzy numberscannot discriminate between two symmetric fuzzy numbers withidentical core. In 200...

fuzzy linear regression models are used to obtain an appropriate linear relation between a dependent variable and several independent variables in a fuzzy environment. several methods for evaluating fuzzy coefficients in linear regression models have been proposed. the first attempts at estimating the parameters of a fuzzy regression model used mathematical programming methods. in this the...