• International Journal of Fuzzy Logic and Intelligent Systems
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• 제15권3호
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• pp.208-215
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• 2015

Since upper and lower approximations could be induced from the rough set structures, rough sets are considered as approximations. The concept of fuzzy rough sets was proposed by replacing crisp binary relations with fuzzy relations by Dubois and Prade. In this paper, we introduce and investigate some properties of intuitionistic fuzzy rough approximation operators and intuitionistic fuzzy relations by means of topology.

• 산업경영시스템학회지
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• 제34권2호
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• pp.30-34
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• 2011

Variable precision rough set models have been successfully applied to problems whose domains are discrete values. However, there are many situations where discrete data is not available. When it comes to the problems with interval values, no variable precision rough set model has been proposed. In this paper, we propose a variable precision rough set model for interval values in which classification errors are allowed in determining if two intervals are same. To build the model, we define equivalence class, upper approximation, lower approximation, and boundary region. Then, we check if each of 11 characteristics on approximation that works in Pawlak's rough set model is valid for the proposed model or not.

• Korean Journal of Mathematics
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• 제29권1호
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• pp.81-89
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• 2021

In this paper, we introduce the notions of a distance function, Alexandrov topology and ⊖-upper (⊕-lower) approximation operator based on complete co-residuated lattices. Under various relations, we define (⊕, ⊖)-fuzzy rough set on complete co-residuated lattices. Moreover, we study their properties and give their examples.

• 한국지능시스템학회논문지
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• 제11권5호
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• pp.441-447
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• 2001

In general, Rough Set theory is used for classification, inference, and decision analysis of incomplete data by using approximation space concepts in information system. Information system can include quantitative attribute values which have interval characteristics, or incomplete data such as multiple or unknown(missing) data. These incomplete data cause tole inconsistency in information system and decrease the classification ability in system using Rough Sets. In this paper, we present various types of incomplete data which may occur in information system and propose INcomplete information Processing System(INiPS) which converts incomplete information system into complete information system in using Rough Sets.

• 한국음향학회지
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• 제28권3호
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• pp.174-186
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• 2009

경계면이 존재하는 해양에서의 수중 음파 전달 모델링 시 일반적으로 평평한 경계면을 가정하고 Rayleigh가 제안했던 반사계수를 이용해 반사파를 계산할 수 있다. 하지만 해수면이나 해저면과 같은 실제 해양의 경계면은 불규칙적인 거칠기를 가진다. 이러한 경계면에서의 반사 손실은 실험식이나 산란 이론에 기반한 간섭 반사 계수를 계산하여 구할 수 있다. 본 논문에서는 섭동 이론, Kirchhoff 근사법, 작은 가지 근사법과 같은 산란 이론을 이용하여 유체-유체 경계면에 대한 간섭 반사 계수를 각각 유도한다. 이를 이용하여 임의의 거칠기를 가지는 해수면과 해저면에 대한 각 산란 이론의 간섭 반사계수를 계산하며, 이 결과를 Rayleigh 반사 계수와 비교하여 경계면의 거칠기에 따른 반사 손실을 분석한다. 또한, 섭동 이론과 Kirchhoff 근사법의 결과를 일반적으로 적용 범위가 넓은 작은 기울기 근사법의 결과와 비교하여 각 이론의 유효범위에 대해 고찰한다.

• 전자공학회논문지A
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• 제32A권1호
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• pp.45-52
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• 1995

A new Kirchhoff approximation(KA) method was proposed for microwave scttering from randomly rough surfaces. Using the spectral representation of delta function and its sifting theorem, a new KA was formulated directly without any further approximation, and this formulated was used to compute exact backscttering coefficients. The validity of the KA was verified by a numerical method, and this new KA technique was used to evaluate the existing approximated KkA methods; i.t., the zeroth-order and the first-order approximated physical optics(PO) models. It was shown that the first-order approximated PO model has small error than the zeroth-order approximated PO model at low incidence angles and the opposite happens at higher incidence angles. This new KA model can be used to compute exact scattering coefficients in the validity regions of KA and to evaluate other theoretical and numerical models for scattering from randomly rough surfaces.

• Korean Journal of Mathematics
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• 제25권1호
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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.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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• pp.337-339
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• 1996

In this paper, we construct rough relational database model using approximation concepts of rough set. Also, we analyze the relation between objects, attributes and attribute values and, propose the method that can generate flexible retrieval results.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권1호
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• pp.57-65
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• 2014

In this paper, we investigate the properties of L-lower approximation operators as a generalization of fuzzy rough set in complete residuated lattices. We study relations lower (upper, join meet, meet join) approximation operators and Alexandrov L-topologies. Moreover, we give their examples as approximation operators induced by various L-fuzzy relations.

• 한국컴퓨터정보학회논문지
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• 제1권1호
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• pp.183-188
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• 1996

Zadeh에 의하여 소개된 퍼지 집합은 소속 함수를 이용하여 애매한 정보처리 및 추론을 가능토록 한 개념이다 Rough 집합의 개념은 Pawlak에 의하여 소개 되었으며.식별 곤란한 데이터의 분류, 축소 및 근사추론을 가능토록 한다. Pawlakl은 퍼지 집합과 Hough 집합을 서로 다른 개념으로 비교하여 서로 결합할 수 없는 것으로 정의하였다. 본 논문의 목적은 Pawlak의 정의와는 달리 퍼지 집합의 소속 함수를 Rough 집합에 적용함으로써 퍼지 집합과 Rough집합을 결합한 퍼지-rough집합의 개념을 정립하기 위한 것이다.