On the nearest parametric approximation of a fuzzy number—Revisited

The problem of finding the nearest parametric approximation of a fuzzy number with respect to the average Euclidean distance is completely solved. Properties of translation invariance, scale invariance, additivity, preservation of expected value, value and ambiguity of this new approximation operator are studied and an algorithm for computing it is provided.     

Metric properties of the nearest extended parametric fuzzy number and applications

We propose the notion of extended parametric fuzzy number, which generalizes the extended trapezoidal fuzzy number and parametric fuzzy number, discussed in some recent papers. The metric properties of the nearest extended parametric fuzzy number of a fuzzy number, proved in the present article, help us to obtain the property of continuity for the parametric approximation operator and to simplify the solving of the problems of parametric approximations under conditions.     

Nearest interval approximation of a fuzzy number

The problem of the interval approximation of fuzzy numbers is discussed. A new interval approximation operator, which is the best one with respect to a certain measure of distance between fuzzy numbers, is suggested.     

Parameterized approximation of fuzzy number with minimum variance weighting functions

In the parameterized fuzzy number expectation and fuzzy number interval approximation with the weighting function method, we once considered the weighting function form with maximum entropy, which has some interesting properties. In the present paper, we will propose another kind of parameterized weighting function with minimum variance, and apply it to the fuzzy number expectation and fuzzy number interval approximation problems. It shows that the minimum variance weighting function also has some similar interesting properties, and can be used to express the decision maker’s preference information in the fuzzy number defuzzification process.     

Ranking fuzzy numbers by distance minimization

In this paper, we proposed a defuzzification using minimizer of the distance between the two fuzzy numbers. Then, we obtain the nearest point with respect to a fuzzy numbers and by considering the nearest point, we can present a ranking method for the fuzzy numbers. Also we give two new properties for ordering. Theorems and remarks are proposed for existence and uniqueness of the nearest point. The method is illustrated by numerical examples and compared with other methods.     

Approximation of fuzzy numbers by trapezoidal fuzzy numbers preserving the expected interval

The problem to find the nearest trapezoidal approximation of a fuzzy number with respect to a well-known metric, which preserves the expected interval of the fuzzy number, is completely solved. The previously proposed approximation operators are improved so as to always obtain a trapezoidal fuzzy number. Properties of this new trapezoidal approximation operator are studied.     

The possibilistic moments of fuzzy numbers and their applications

This paper, introduces the nearest weighted interval and point approximations of a fuzzy number, and then suggests weighted possibilistic moments about these points of fuzzy numbers. The possibilistic moments play an important role in fuzzy sets and systems, specifically in physics, mathematics and statistics. We provide the definition of the moments of fuzzy numbers as well as the definition of moments in probability theory; some of their applications are mentioned.     

A note on “Generalized fuzzy rough approximation operators based on fuzzy coverings”

In this note, we show by examples that Theorem 5.3, partial proof of Theorem 5.3′, Lemma 5.4 and Remark 5.2 in [1] contain slight flaws and then provide the correct versions.     

Triangular and parametric approximations of fuzzy numbers—inadvertences and corrections

Recent papers were dedicated to approximate fuzzy numbers by triangular, trapezoidal or parametric fuzzy numbers, with or without additional conditions. Unfortunately, the result of approximation is not always a fuzzy number, sometimes it is not a fuzzy set. We point out the wrongs and inadvertences in some recent papers, then we correct the results.     

On the fuzzy solution of LR fuzzy linear systems

In this paper, the solution of fuzzy linear system (FLS) is investigated based on a 1$1$-level expansion. To this end, 1$1$-level of FLS is solved for calculating the core of fuzzy solution and then its spreads are obtained by solving an optimization problem with a special objective function. Using our proposed method, if the computed solution satisfies the FLS, it can be as exact or approximated solution. Finally, the existence of solution of FLS is proved in details and some numerical examples are solved to illustrate the accuracy and capability of the method.     

Sensitivity analysis in interval-valued trapezoidal fuzzy number linear programming problems

The aim of this article is to introduce a formulation of fuzzy linear programming problems involving the level (h^L,h^U)$(h^L\text{,}{h}^U)$-interval-valued trapezoidal fuzzy numbers as parameters. Indeed, such a formulation is the general form of trapezoidal fuzzy number linear programming problems. Then, it is demonstrated that study of the sensitivity analysis for the level (h^L,h^U)$(h^L\text{,}{h}^U)$-interval-valued trapezoidal fuzzy number linear programming problems gives rise to the same expected results as those obtained for trapezoidal fuzzy number linear programming problems.     

On the number of segments needed in a piecewise linear approximation

The introduction of high-speed circuits to realize an arithmetic function f as a piecewise linear approximation has created a need to understand how the number of segments depends on the interval a≤x≤b and the desired approximation error ε. For the case of optimum non-uniform segments, we show that the number of segments is given as , (ε→0⁺), where . Experimental data shows that this approximation is close to the exact number of segments for a set of 14 benchmark functions. We also show that, if the segments have the same width (to reduce circuit complexity), then the number of segments is given by , (ε→0⁺), where .     

On fuzzy metric spaces

In this paper we introduce the concept of a fuzzy metric space. The distance between two points in a fuzzy metric space is a non-negative, upper semicontinuous, normal and convex fuzzy number. Properties of fuzzy metric spaces are studied and some fixed point theorems are proved.     

On best rational approximation of analytic functions

This paper contains some theorems related to the best approximation ρ_n(f;E) to a function f in the uniform metric on a compact set by rational functions of degree at most n. We obtain results characterizing the relationship between ρ_n(f;K) and ρ_n(f;E) in the case when complements of compact sets K and E are connected, K is a subset of the interior Ω of E, and f is analytic in Ω and continuous on E.     

On strong consistency of the fuzzy generalized nearest neighbor rule

The k nearest neighbor rule (k-NNR) is a well-known nonparametric decision rule in pattern classification. Fuzzy set theory has been widely used to represent the uncertainty of class membership. Several researchers extended conventional k-NNR to fuzzy k-NNR, such as Bezdek et al. [Fuzzy Sets and Systems 18 (1986) 237–256], Keller et al. [IEEE Trans. Syst. Man, and Cybern. 15(4) (1985) 580–585], Béreau and Dubuisson [Fuzzy Sets and Systems 44 (1991) 17–32]. In this paper, we describe a fuzzy generalized k-NN algorithm. This algorithm is a unified approach to a variety of fuzzy k-NNR's. Then we create the strong consistency of posterior risk of the fuzzy generalized NNR.     

An approach for solving a fuzzy multiobjective programming problem

In this paper we present a new approach, based on the Nearest Interval Approximation Operator, for dealing with a multiobjective programming problem with fuzzy-valued objective functions.