• Journal of the Korea Society of Computer and Information
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• v.1 no.1
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• pp.183-188
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• 1996

Fuzzy sets Introduced by Zadeh is a concept which can process, and reson a vague Information using membership functions. The notion of rough sets introduced by Pawlak is based on the ability to classify. reduce. and perform approximation reasoning for the Indiscernible data.A comparison between fuzzy sets and rough sets has been given In Pawlak where it is shown that these concepts are different and can't combine each other. The purpose of this paper Is to Introduce and define the notion of fuzzy-rough sets which joins the membership function of fuzzy sets to the rough sets.

• Journal of applied mathematics & informatics
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• v.38 no.3_4
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• pp.335-349
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• 2020

We present inverse soft rough sets by using inverse soft sets and soft rough sets. We study different approaches for inverse soft rough set and examine the relationships between them. We also discuss and explore the basic properties for these approaches. Moreover we develop an algorithm following these concepts and apply it to a decision-making problem to demonstrate the applicability of the proposed methods.

• The Transactions of the Korea Information Processing Society
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• v.4 no.1
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• pp.1-10
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• 1997

In this paper, for useful administration of the data which have ambiguities meaningfully and hard to treat, a new relation database model using an integrated fuzzy sets and rough sets relational database one. After proposing Fuzzy-rough relational database model on the base of integrated Fuzzy and Rough sets, Application of the examples of arithmetic is analyzed through the Access DBMS and the visual basic by composing and representing database based on fuzzy and rough sets which are characterized as fuzzy sets and rough sets on Pentium computer(166Mhz). This paper was induced to reduce the data incompleteness.

• Journal of the Ergonomics Society of Korea
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• v.29 no.4
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• pp.631-637
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• 2010

The aim of affective engineering is to develop a new product by translating customer affections into design factors. Affective data have so far been analyzed using a multivariate statistical analysis, but the affective data do not always have linear features assumed under normal distribution. Rough sets model is an effective method for knowledge discovery under uncertainty, imprecision and fuzziness. Rough sets model is to deal with any type of data regardless of their linearity characteristics. Therefore, this study utilizes rough sets model to extract affective knowledge from affective data. Four types of scent alternatives and four types of sounds were designed and the experiment was performed to look into affective differences in subject's preference on air conditioner. Finally, the purpose of this study also is to extract knowledge from affective data using rough sets model and to figure out the relationships between rough sets based affective engineering method and statistical one. The result of a case study shows that the proposed approach can effectively extract affective knowledge from affective data and is able to discover the relationships between customer affections and design factors. This study also shows similar results between rough sets model and statistical method, but it can be made more valuable by comparing fuzzy theory, neural network and multivariate statistical methods.

• Communications of the Korean Mathematical Society
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• v.25 no.4
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• pp.511-522
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• 2010

Rough sets, rough quick ideals and rough fuzzy quick ideals in d-algebras are established, and some related properties are investigated.

• Honam Mathematical Journal
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• v.32 no.2
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• pp.203-215
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• 2010

The notion of strong ideal in BH-algebra is introduced and investigated some properties of it. Rough sets and rough strong ideals in BH-algebras are established and some related their properties are discussed.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.3
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• pp.16-25
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• 1998

In this paper, we propose features extraction method using Rough sets theory for efficient data classifications in hyperspectral environment. First, analyze the properties of multispectral image data, then select the most efficient bands using discemibility of Rough sets theory based on analysis results. The proposed method is applied Landsat TM image data, from this, we verify the equivalence of traditional bands selection method by band features and bands selection method using Rough sets theory that pmposed in this paper. Finally, we present theoretical basis to features extraction in hyperspectral environment.

• Korean Journal of Mathematics
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• v.19 no.2
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• pp.219-232
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• 2011

We investigated the properties of rough approximations induced by two families of preordered sets and closure systems. We study the relations among the lower and upper rough approximations, closure and interior systems, preordered sets.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.299-304
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• 2011

In this paper, we investigate the properties of rough approximations defined by preordered sets. We study the relations among the lower and upper rough approximations, closure and interior systems, and closure and interior operators.

• 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.