Currently displaying 1 – 8 of 8

Showing per page

Order by Relevance | Title | Year of publication

A convergence of fuzzy random variables

Dug Hun Hong — 2003

Kybernetika

In this paper, a general convergence theorem of fuzzy random variables is considered. Using this result, we can easily prove the recent result of Joo et al, which gives generalization of a strong law of large numbers for sums of stationary and ergodic processes to the case of fuzzy random variables. We also generalize the recent result of Kim, which is a strong law of large numbers for sums of levelwise independent and levelwise identically distributed fuzzy random variables.

An additive decomposition of fuzzy numbers

Dug Hun Hong — 2003

Kybernetika

Hong and Do[4] improved Mareš[7] result about additive decomposition of fuzzy quantities concerning an equivalence relation. But there still exists an open question which is the limitation to fuzzy quantities on R (the set of real numbers) with bounded supports in the presented theory. In this paper we restrict ourselves to fuzzy numbers, which are fuzzy quantities of the real line R with convex, normalized and upper semicontinuous membership function and prove this open question.

On types of fuzzy numbers under addition

Dug Hun Hong — 2004

Kybernetika

We consider the question whether, for given fuzzy numbers, there are different pairs of t -norm such that the resulting membership function within the extension principle under addition are identical. Some examples are given.

The stability of parameter estimation of fuzzy variables

Dug Hun Hong — 2009

Kybernetika

Recently, the parameter estimations for normal fuzzy variables in the Nahmias’ sense was studied by Cai [4]. These estimates were also studied for general T -related, but not necessarily normal fuzzy variables by Hong [10] In this paper, we report on some properties of estimators that would appear to be desirable, including unbiasedness. We also consider asymptotic or “large-sample” properties of a particular type of estimator.

Page 1

Download Results (CSV)