نتایج جستجو برای: fuzzy number function
تعداد نتایج: 2299648 فیلتر نتایج به سال:
the supplier selection is a multi-criteria decision making which consist both qualities and quantities metrics. a lot of investigations have been published in the supplier selection area and, most of the proposed models focused on manufacturing environments and a few papers have been allocated for service industries. proposed system utilizes new method that transfer the house of quality (hoq) a...
in this paper, a new structure possessing the advantages of low-power consumption, less hardware and high-speed is proposed for fuzzy controller. the maximum output delay for general fuzzy logic controllers (flc) is about 86 ns corresponding to 11.63 mflips (fuzzy logic inference per second) while this amount of the delay in the designed fuzzy controller becomes 52ns that corresponds to 19.23 m...
as we know, developing mathematical models and numerical procedures that would appropriately treat and solve systems of linear equations where some of the system's parameters are proposed as fuzzy numbers is very important in fuzzy set theory. for this reason, many researchers have used various numerical methods to solve fuzzy linear systems. in this paper, we define the concepts of midpoint a...
in this paper, we propose a numerical method for the approximate solution of fuzzy Fredholm functional integral equations of the second kind by using an iterative interpolation. For this purpose, we convert the linear fuzzy Fredholm integral equations to a crisp linear system of integral equations. The proposed method is illustrated by some fuzzy integral equations in numerical examples. Keywor...
In this paper we study some models for dealing with Fuzzy Integer Linear Programming problems which have a certain lack of precision of a vague nature in their formulation. We present methods to solve them with either fuzzy constraints, or fuzzy numbers in the objective function or fuzzy numbers defining the set of constraints. These methods are based on the representation theorem and on fuzzy ...
a general approach to linguistic approximation and its application in frame of fuzzy logic deduction
this paper deals with one problem that needs to be addressed in the emerging field known under the name computing with perceptions. it is the problem of describing, approximately, a given fuzzy set in natural language. this problem has lately been referred to as the problem of retranslation. an approaches to dealing with the retranslation problem is discussed in the paper, that ...
This paper attempts to present the new approach to design sufficient number of systematic fuzzy linguistics in matrix form and map the Fuzzy Linguistic Variable Matrix, which contains linguistic terms, into numeric domain using Fuzzy Normal Distribution based on the Parabola-based Membership Function. Existing fuzzy set theory is difficult to design the systematic and sufficient fuzzy linguisti...
2. Fuzzy stochastic processes First we give some mathematical notations regarding fuzzy numbers. Let (Ω,M, P ) be a probability space, where M is a σ-field and P is a non-atomic probability measure. R denotes the set of all real numbers, and let C(R) be the set of all non-empty bounded closed intervals. A ‘fuzzy number’ is denoted by its membership function ã : R → [0, 1] which is normal, upper...
Type-II fuzzy sets are used to convey the uncertainties in the membership function of type-I fuzzy sets. Linguistic information in expert rules does not give any information about the geometry of the membership functions. These membership functions are mostly constructed through numerical data or range of classes. But there exists an uncertainty about the shape of the membership, that is, wheth...
Robust regression is an appropriate alternative for ordinal regression when outliers exist in a given data set. If we have fuzzy observations, using ordinal regression methods can't model them; In this case, using fuzzy regression is a good method. When observations are fuzzy and there are outliers in the data sets, using robust fuzzy regression methods are appropriate alternatives....
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