Recently Abbasbandy and Hajjari (Computers and Mathematics with Applications57 (2009) 413-419) have introduced a ranking method for the trapezoidalfuzzy numbers. This paper extends theirs method to all fuzzy numbers,which uses from a defuzzication of fuzzy numbers and a general weightingfunction. Extended method is interesting for ranking all fuzzy numbers, and itcan be applied for solving and ...

‎a new method for the defuzzification of fuzzy numbers is developed in this paper. it is well-known, defuzzification methods allow us to find aggregative crisp numbers or crisp set for fuzzy numbers. but different fuzzy numbers are often converted into one crisp number. in this case the loss of essential information is possible. it may result in inadequate final conclusions, for example, expert...

Many variants of fuzzy c-means (FCM) clustering method are applied to crisp numbers but only a few of them are extended to non-crisp numbers, mainly due to the fact that the latter needs complicated equations and exhausting calculations. Vector form of fuzzy c-means (VFCM), proposed in this paper, simplifies the FCM clustering method applying to non-crisp (symbolic interval and fuzzy) numbers. ...

abstract background and purpose: since protein a is considered an important protein from medical, medicinal, genetic engineering, and biotechnology point of view, the present study attempted to investigate and determine to what extent protein a is produced through regression, in addition to the production conditions of the protein. thus, a figure was introduced as for the estimation of the amou...

Ranking fuzzy numbers plays a very important role in linguistic decision making and other fuzzy application systems. In spite of many ranking methods, no one can rank fuzzy numbers with human intuition consistently in all cases. Shortcoming are found in some of the convenient methods for ranking triangular fuzzy numbers such as the coefficient of variation (CV index), distance between fuzzy set...

in this paper, we study the existence, asymptotic behavior of the positive solutions of a fuzzy nonlinear difference equation$$ x_{n+1}=frac{ax_n+x_{n-1}}{b+x_{n-1}}, n=0,1,cdots,$$ where $(x_n)$ is a sequence of positive fuzzy number, $a, b$ are positive fuzzy numbers and the initial conditions $x_{-1}, x_0$ are positive fuzzy numbers.

In the fuzzy arithmetic, the definitions of addition and multiplication of fuzzy numbers are based on Zadeh’s extension principle. From theoretical and practical points of view, this multiplication of fuzzy numbers owns several unnatural properties. Recently, to avoid this shortcoming, a new multiplicative operation of product type is introduced, the so-called cross-product of fuzzy numbers. Th...