نتایج جستجو برای: triangular tfns and trapezoidal tpfns fuzzy numbers

تعداد نتایج: 16870558  

Journal: :Fuzzy Sets and Systems 2006
Richard Y. K. Fung Yizeng Chen Jiafu Tang

Product planning is one of four important processes in new product development (NPD) using quality function deployment (QFD), which is a widely used customer-driven approach. In our opinion, the first problem to be solved is how to incorporate both qualitative and quantitative information regarding relationships between customer requirements (CRs) and engineering characteristics (ECs) as well a...

Journal: :journal of mahani mathematical research center 0
saed f. mallak palestine technical university -kadoorie department of applied mathematics duha m. bedo palestine technical university -kadoorie department of applied mathematics

in a previous work, we introduced particular fuzzy numbers anddiscussed some of their properties. in this paper we use the comparison methodintroduced by dorohonceanu and marin[5] to compare between these fuzzynumbers.

2012
Palash Dutta Tazid Ali

Risk assessment is a popular and important tool in decision making process. Risk assessment is generally performed using models and model is a function of some parameters which are usually affected by uncertainty. Here, we consider that model parameters are affected by epistemic uncertainty. To represent epistemic uncertainty in general triangular fuzzy number or trapezoidal fuzzy numbers are u...

2013
S. Narayanamoorthy

The basic transportation problem was originally developed by Hitchcock. In the literature several methods are proposed for solving Fuzzy transportation problem. In this paper, we propose a new algorithm called Fuzzy Russell’s method for the initial basic feasible solution to a Fuzzy transportation problem. To examine the proposed method a numerical example is solved. Fuzzy numbers may be normal...

2008
T. Razzaghnia E. Pasha E. Khorram

In this paper, we aim to extended the constraints of Tanaka’s model. Applied coefficients of the fuzzy regression by them is the symmetric triangular fuzzy numbers, while we try to replace it by more general asymmetric trapezoidal one. Possibility of two asymmetric trapezoidal fuzzy numbers is explained by possibility distribution. Two different models is presented and a numerical example is gi...

2008
Ting-Yu Chen Tai-Chun Ku

The weight is one of the most useful tools to measure the attribute importance when individuals make a decision or evaluate the alternatives. Among the methods which measure the weight, fuzzy measures is are subjective scales for the degrees of fuzziness and widely used to determine the degrees of subjective importance of evaluation items in numerous studies for the time being. The purpose of t...

2006
Barnabás Bede János Fodor

Multiplicative operations for fuzzy numbers raise several problems both from the theoretical and practical point of view in fuzzy arithmetic. The multiplication based on Zadeh's extension principle and its triangular and trapezoidal approximation is used in several recent works in applications in geology. Recently, new product-type operation are introduced and studied, as e.g. the cross product...

2012
Neha Bhatia Amit Kumar

In previous studies, it is pointed out that in several situations it is better to use interval-valued fuzzy numbers instead of triangular or trapezoidal fuzzy numbers. But till now, there is no method that deals with the sensitivity analysis of such linear programming problems in which all the parameters are represented by interval-valued fuzzy numbers. In this paper, a new method is proposed f...

2015
Ashwani Kharola

This paper illustrates a Comparative study of highly non-linear, complex and multivariable Inverted Pendulum (IP) system on Cart using different soft computing techniques. Firstly, a Fuzzy logic controller was designed using triangular and trapezoidal shape Membership functions (MF's). The trapezoidal fuzzy controller shows better results in comparison to triangular fuzzy controller. Secondly, ...

2005
Arnold F. Shapiro

Recent articles, such as McCauley-Bell et al. (1999) and Sánchez and Gómez (2003a, 2003b, 2004), used fuzzy regression (FR) in their analysis. Following Tanaka et. al. (1982), their regression models included a fuzzy output, fuzzy coefficients and an nonfuzzy input vector. The fuzzy components were assumed to be triangular fuzzy numbers (TFNs). The basic idea was to minimize the fuzziness of th...

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