• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.655-659
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• 2004

In this literature, the selection of data set among the universe set is carried out with the fuzzy entropy function. By the definition of fuzzy entropy, the fuzzy entropy function is proposed and the proposed fuzzy entropy function is proved through the definition. The proposed fuzzy entropy function calculate the certainty or uncertainty value of data set, hence we can choose the data set that satisfying certain bound or reference. Therefore the reliable data set can be obtained by the proposed fuzzy entropy function. With the simple example we verify that the proposed fuzzy entropy function select reliable data set.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.269-274
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• 2009

Measuring uncertainty for fuzzy sets has been carried out by calculating fuzzy entropy. Fuzzy entropy of fuzzy set is derived with the help of distance measure. The distance proportional value between the fuzzy set and the corresponding crisp set is designed as the fuzzy entropy. The usefulness is verified by proving the proposed entropy. Generally, fuzzy entropy contains the complementary characteristics that the fuzzy entropies of fuzzy set and complementary fuzzy set have the same entropies. Discrepancy that low fuzzy entropy did not guarantee the data certainty was overcome by modifying fuzzy entropy formulation. Obtained fuzzy entropy is analyzed and discussed through simple example.

• Journal of KIISE:Software and Applications
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• v.27 no.7
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• pp.723-730
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• 2000

Fuzzy numbers represent fuzzy numeric values. However, it is difficult to clearly determine whether one fuzzy number is larger or smaller than other fuzzy numbers. Thus it is also difficult to determine the rank which a fuzzy number takes, or to select the k-th largest fuzzy number in a given set of fuzzy numbers. In this paper, we propose a fuzzy set based method to determine the rank of a fuzzy number and the k-th largest fuzzy number. The proposed method uses a given fuzzy greater-than relation which is defined on a set of fuzzy numbers. Our method describes the rank of a fuzzy number with a fuzzy set of ranks that the fuzzy number can take, and the k-th largest fuzzy number with a fuzzy set of fuzzy numbers which can be k-th ranked.

• Journal of applied mathematics & informatics
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• v.35 no.3_4
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• pp.331-347
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• 2017

Soft sets are fantastic mathematical tools to handle imprecise and uncertain information in complicated situations. In this paper, we defined the hybrid structure which is the combination of soft set and complex number representation of intuitionistic fuzzy set. We defined basic set theoretic operations such as complement, union, intersection, restricted union, restricted intersection etc. for this hybrid structure. Moreover, we developed this theory to establish some more set theoretic operations like Disjunctive sum, difference, product, conjugate etc.

• Journal of applied mathematics & informatics
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• v.7 no.1
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• pp.335-346
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• 2000

This paper discusses the relation of fuzzy sets satisfying some types of fuzzy covering properties. We give some characterizations of such fuzzy sets and investigate a few properties.

• Korean Journal of Mathematics
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• v.25 no.1
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• pp.71-85
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• 2017

This paper introduces a novel extension of soft rough fuzzy set so-called modified soft rough fuzzy set model in which new lower and upper approximation operators are presented together their related properties that are also investigated. Eventually it is shown that these new models of approximations are finer than previous ones developed by using soft rough fuzzy sets.

• Korean Journal of Mathematics
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• v.17 no.4
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• pp.361-374
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• 2009

We characterize a fuzzy partial order relation using its level set, find sufficient conditions for the image of a fuzzy partial order relation to be a fuzzy partial order relation, and find sufficient conditions for the inverse image of a fuzzy partial order relation to be a fuzzy partial order relation. Also we define a fuzzy lattice as fuzzy relations, characterize a fuzzy lattice using its level set, show that a fuzzy totally ordered set is a distributive fuzzy lattice, and show that the direct product of two fuzzy lattices is a fuzzy lattice.

• Journal of Applied and Pure Mathematics
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• v.5 no.1_2
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• pp.121-128
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• 2023

The aim of this article is to extend hesitant fuzzy minimal open and hesitant fuzzy maximal open sets in hesitant fuzzy topological space. Further, we investigate some properties with these new sets.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.1
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• pp.79-86
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• 2015

This paper is devoted to finding relationship between intuitionistic fuzzy preorders and intuitionistic fuzzy topologies. For any intuitionistic fuzzy preordered space, an intuitionistic fuzzy topology will be constructed. Conversely, for any intuitionistic fuzzy topological space, we obtain an intuitionistic fuzzy preorder on the set. Moreover, we will show that the family of all intuitionistic fuzzy preorders on an underlying set has a very close link to the family of all intuitionistic fuzzy topologies on the set satisfying some extra condition.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.389-394
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• 2011

The notion of generalized intuitionistic fuzzy soft set theory is proposed. Our generalized intuitionistic fuzzy soft set theory is a combination of the generalized intuitionistic fuzzy set theory and the soft set theory. In other words, our generalized intuitionistic fuzzy soft set theory is an extension of the intuitionistic fuzzy soft set theory. The complement, "and" and "or" operations are defined on the generalized intuitionistic fuzzy soft sets. Their basic properties for the generalized intuitionistic fuzzy soft sets are also presented and discussed.