نتایج جستجو برای: fuzzy distance function fuzzy metric

تعداد نتایج: 1557331  

This paper addresses the design of control charts for both variable ( x chart) andattribute (u and c charts) quality characteristics, when there is uncertainty about the processparameters or sample data. Derived control charts are more flexible than the strict crisp case, dueto the ability of encompassing the effects of vagueness in form of the degree of expert’spresumption. We extend the use o...

2013
Reza Ezzati Maryam Bagherian

In this paper, we prove a general form of a fixed point theorem with contractive-like mapping defined by altering function. We also present its application on study of existence and uniqueness of solution of fuzzy initial value problems in fuzzy partial metric spaces. In order to do this, we recall some fixed point theorems in partial metric spaces either crisp or fuzzy and use these theorems t...

2013
Syed Shahnawaz Ali Jainendra Jain Anil Rajput

Fuzzy Mathematics has seen an enormous growth since the introduction of notion of fuzzy sets by Zadeh in 1965. Kramosil and Michalek introduced the notion of fuzzy metric spaces which was later modified by George and Veeramani and others. The notion of intuitionistic fuzzy metric spaces was introduced by Park in 2004. Many authors have studied fixed point and common fixed theorems for mappings ...

Journal: :Fuzzy Sets and Systems 2010
Jesús Rodríguez-López Salvador Romaguera José Manuel Sánchez-Álvarez

Removing the condition of symmetry in the notion of a fuzzy (pseudo)metric, in Kramosil and Michalek’s sense, one has the notion of a fuzzy quasi-(pseudo-)metric. Then for each fuzzy quasi-pseudo-metric on a set X we construct a fuzzy quasipseudo-metric on the collection of all nonempty subsets of X, called the Hausdorff fuzzy quasi-pseudo-metric. We investigate several properties of this struc...

In this paper, we introduce a new concept of fuzzy generalizedcontraction and give a fixed point result for such mappings in the setting of fuzzy M-complete metric spaces. We also give an affirmative partial answer to a question posed by Wardowski [D. Wardowski, Fuzzy contractive mappings and fixed points in fuzzy metric spaces, Fuzzy Set Syst., {bf 222}(2013), 108-114].Some examples are also g...

2015
Núria Agell Mónica Sánchez Francesc Prats Francisco Javier Ruiz

Given a finite totally ordered set of linguistic terms, the operations intersection and connected union provide a lattice structure to the set of hesitant fuzzy linguistic term sets. In this framework, hesitant fuzzy linguistic descriptions of a given set of alternatives are considered. A distance between hesitant fuzzy linguistic descriptions is introduced based on the properties of the lattic...

2012
Yonghong Shen Haifeng Li Faxing Wang

In this paper, following the ideas of (continuous) t-norm and interval numbers, a concept of (continuous) interval-valued t-norm is proposed. Based on the interval-valued fuzzy set and the continuous interval-valued t-norm, we propose a notion of interval-valued fuzzy metric space, which is a generalization of fuzzy metric space in the sense of George and Veeramani [Fuzzy Sets and Systems 64 (1...

Journal: :Journal of the Operations Research Society of Japan 2017

Journal: :iranian journal of fuzzy systems 2014
d. qiu c. lu w. zhang

in this paper,  we provide two different kinds of fixed pointtheorems in  fuzzy metric spaces. the first kind is for the fuzzy$varepsilon$-contractive type mappings and  the second kind is forthe fuzzy order $psi$-contractive type mappings. they improve thecorresponding  conclusions in the literature.

A. A. Hosseinzadeh, M. A. Jahantigh, M. Khezerloo, S. Khezerloo,

In this work, we propose an approach for computing the compromised solution of an LR fuzzy linear system by using of a ranking function when the coefficient matrix is a crisp mn matrix. To do this, we use expected interval to find an LR fuzzy vector, X , such that the vector (AX ) has the least distance from (b) in 1 norm and the 1 cut of X satisfies the crisp linear system AX = b ...

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