kim and bishu (fuzzy sets and systems 100 (1998) 343-352) proposeda modification of fuzzy linear regression analysis. their modificationis based on a criterion of minimizing the difference of the fuzzy membershipvalues between the observed and estimated fuzzy numbers. we show that theirmethod often does not find acceptable fuzzy linear regression coefficients andto overcome this shortcoming, pr...

in this paper, we introduce a function in order to measure the distancebetween two order intervals of fuzzy numbers, and show that this function isa metric. we investigate some properties of this metric, and finally presentan application. we think that this study could provide a more generalframework for researchers studying on interval analysis, fuzzy analysis andfuzzy decision making.

Dimensional analysis, for multi-criteria decision making, is a mathematical method that includes diverse heterogeneous criteria into a single dimensionless index. Dimensional Analysis, in its current definition, presents the drawback to manipulate fuzzy information commonly presented in a multi-criteria decision making problem. To overcome such limitation, we propose two dimensional analysis ba...

project participants are becoming more aware of the high costs and risks associated with delay claims and their litigation. among delays, weather delay has an important role in projects performed in severe environmental conditions. this research is the extension of delay analysis techniques by approving analysis of weather delays using fuzzy logic. at the presented technique, first using a fuzz...

introduction: many organizations, especially, service organizations, relative to their goals and mission, have a special view towards quality phenomena and its management and are turning to approaches such as tqm to help manage their business. this study examined the tqm indicators gap in isfahan khorshid hospital. as fuzzy set theory is better than the logical theory for estimating the linguis...

The classification of fuzzy data is considered as the most challenging areas of data analysis and the complexity of the procedures has been obstacle to the development of new methods for fuzzy data analysis. However, there are significant advances in modeling systems in which fuzzy data are available in the field of mathematical programming. In order to exploit the results of the researches on ...

Abshocr-Fuzzy modeling of complex systems is a challenging topic. This paper proposes an effective approach to data-based fuzzy optimizing fuzzy system structure and parameters. For this purpose, we cope with fuzzy clustering based on inclusion concept where the rule-base bas to be simplified. This simplification occurs in the sense that similar Membership Functions (MF) pertaining to the premi...

several practical problems of hypotheses testing can be under a general linear model analysis of variance which would be examined. in analysis of variance, when the response random variable y , has linear relationship with several random variables x, another important model as analysis of covariance can be used. in this paper, assuming that y is fuzzy and using dlr metric, a method for testing ...