• 제목/요약/키워드: rough set

검색결과 258건 처리시간 0.021초

데이터마이닝의 자동 데이터 규칙 추출 방법론 개발 : 계층적 클러스터링 알고리듬과 러프 셋 이론을 중심으로 (Development of Automatic Rule Extraction Method in Data Mining : An Approach based on Hierarchical Clustering Algorithm and Rough Set Theory)

  • 오승준;박찬웅
    • 한국컴퓨터정보학회논문지
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    • 제14권6호
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    • pp.135-142
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    • 2009
  • 테이터 마이닝은 대용량의 데이터 셋을 분석하기 위하여 새로운 이론, 기법, 분석 툴을 제공하는 전산 지능분야의 새로운 영역중 하나이다. 데이터 마이닝의 주요 기법으로는 연관규칙 탐사, 분류, 클러스터링 등이 있다. 그러나 이들 기법을 기존 연구 방법들처럼 개별적으로 사용하는 것보다는 통합화하여 규칙들을 자동적으로 발견해내는 방법론이 필요하다. 이런 데이터 규칙 추출 방법론은 대량의 데이터들을 분석하여 성공적인 의사결정을 내리는데 도움을 줄 수 있기에 많은 분야에 이용될 수 있다. 본 논문에서는 계층적 클러스터링 알고리듬과 러프셋 이론을 이용하여 대량의 데이터로부터 의미 있는 규칙들을 발견해 내는 자동적인 규칙 추출 방법론을 제안한다. 또한 UCI KDD 아카이브에 포함되어 있는 데이터 셋을 이용하여 제안하는 방법에 대하여 실험을 수행하였으며, 실제 생성된 규칙들을 예시하였다. 이들 자동 생성된 규칙들은 효율적인 의사결정에 도움을 준다.

An improvement of LEM2 algorithm

  • The, Anh-Pham;Lee, Young-Koo;Lee, Sung-Young
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2011년도 한국컴퓨터종합학술대회논문집 Vol.38 No.1(A)
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    • pp.302-304
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    • 2011
  • Rule based machine learning techniques are very important in our real world now. We can list out some important application which we can apply rule based machine learning algorithm such as medical data mining, business transaction mining. The different between rules based machine learning and model based machine learning is that model based machine learning out put some models, which often are very difficult to understand by expert or human. But rule based techniques output are the rule sets which is in IF THEN format. For example IF blood pressure=90 and kidney problem=yes then take this drug. By this way, medical doctor can easy modify and update some usable rule. This is the scenario in medical decision support system. Currently, Rough set is one of the most famous theory which can be used for produce the rule. LEM2 is the algorithm use this theory and can produce the small set of rule on the database. In this paper, we present an improvement of LEM2 algorithm which incorporates the variable precision techniques.

소프트 컴퓨팅기술을 이용한 원격탐사 다중 분광 이미지 데이터의 분류에 관한 연구 -Rough 집합을 중심으로- (A Study on Classifications of Remote Sensed Multispectral Image Data using Soft Computing Technique - Stressed on Rough Sets -)

  • 원성현
    • 경영과정보연구
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    • 제3권
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    • pp.15-45
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    • 1999
  • Processing techniques of remote sensed image data using computer have been recognized very necessary techniques to all social fields, such as, environmental observation, land cultivation, resource investigation, military trend grasp and agricultural product estimation, etc. Especially, accurate classification and analysis to remote sensed image da are important elements that can determine reliability of remote sensed image data processing systems, and many researches have been processed to improve these accuracy of classification and analysis. Traditionally, remote sensed image data processing systems have been processed 2 or 3 selected bands in multiple bands, in this time, their selection criterions are statistical separability or wavelength properties. But, it have be bring up the necessity of bands selection method by data distribution characteristics than traditional bands selection by wavelength properties or statistical separability. Because data sensing environments change from multispectral environments to hyperspectral environments. In this paper for efficient data classification in multispectral bands environment, a band feature extraction method using the Rough sets theory is proposed. First, we make a look up table from training data, and analyze the properties of experimental multispectral image data, then select the efficient band using indiscernibility relation of Rough set theory from analysis results. Proposed method is applied to LANDSAT TM data on 2 June 1992. From this, we show clustering trends that similar to traditional band selection results by wavelength properties, from this, we verify that can use the proposed method that centered on data properties to select the efficient bands, though data sensing environment change to hyperspectral band environments.

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Automated Feature-Based Registration for Reverse Engineering of Human Models

  • Jun, Yong-Tae;Choi, Kui-Won
    • Journal of Mechanical Science and Technology
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    • 제19권12호
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    • pp.2213-2223
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    • 2005
  • In order to reconstruct a full 3D human model in reverse engineering (RE), a 3D scanner needs to be placed arbitrarily around the target model to capture all part of the scanned surface. Then, acquired multiple scans must be registered and merged since each scanned data set taken from different position is just given in its own local co-ordinate system. The goal of the registration is to create a single model by aligning all individual scans. It usually consists of two sub-steps: rough and fine registration. The fine registration process can only be performed after an initial position is approximated through the rough registration. Hence an automated rough registration process is crucial to realize a completely automatic RE system. In this paper an automated rough registration method for aligning multiple scans of complex human face is presented. The proposed method automatically aligns the meshes of different scans with the information of features that are extracted from the estimated principal curvatures of triangular meshes of the human face. Then the roughly aligned scanned data sets are further precisely enhanced with a fine registration step with the recently popular Iterative Closest Point (ICP) algorithm. Some typical examples are presented and discussed to validate the proposed system.

범주형 데이터의 러프집합 분석을 통한 의사결정 향상기법 (An Improvement of the Decision-Making of Categorical Data in Rough Set Analysis)

  • 박인규
    • 디지털융복합연구
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    • 제13권6호
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    • pp.157-164
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    • 2015
  • 최적의 의사결정시스템에서 효율적인 정보검색을 위해서는 정보의 감축이 필수적이다. 다양한 종류의 데이터에 존재하는 유용한 정보를 찾는 데이터 마이닝 기법에 대한 많은 연구가 활발하게 진행되어 왔고 타 산업과의 융복합을 위한 빅데이터 활용이 높아져 가고 있다. 유용한 지식의 발견을 위한 여러 가지 기법들이 특징을 가지고 있지만 단점이 존재하기 마련이다. 따라서 그러한 특징을 수렴하는 하나의 새로운 기법이 필요하다. 본 논문에서는 베이지언 정리를 이용하여 정보의 대수학적인 확률을 측정하고 이 확률에 대하여 정보엔트로피를 계산함으로써 정보의 불확실성을 계산한다. 제안된 척도를 기반으로 불필요한 속성을 제거하여 최소의 리덕트를 생성하고 이를 기반으로 결정규칙을 유도하는 알고리즘을 제안한다. 제안된 방법의 효율성을 위하여 콘텍트 렌즈를 결정하는 실험을 통하여 기존방법과 비교 결과, 본 연구가 의사결정의 유용성면에 있어 일반성이 있음을 보인다.

GLOBAL SHAPE OF FREE BOUNDARY SATISFYING BERNOULLI TYPE BOUNDARY CONDITION

  • Lee, June-Yub;Seo, Jin-Keun
    • 대한수학회지
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    • 제37권1호
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    • pp.31-44
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    • 2000
  • We study a free boundary problem satisfying Bernoulli type boundary condition along which the gradient of a piecewise harmonic solution jumps zero to a given constant value. In such problem, the free boundary splits the domain into two regions, the zero set and the harmonic region. Our main interest is to identify the global shape and the location of the zero set. In this paper, we find the lower and the upper bound of the zero set. In a convex domain, easier estimation of the upper bound and faster disk test technique are given to find a rough shape of the zero set. Also a simple proof on the convexity of zero set is given for a connected zero set in a convex domain.

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Some Properties of Alexandrov Topologies

  • Kim, Yong Chan;Kim, Young Sun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제15권1호
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    • pp.72-78
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    • 2015
  • Alexandrov topologies are the topologies induced by relations. This paper addresses the properties of Alexandrov topologies as the extensions of strong topologies and strong cotopologies in complete residuated lattices. With the concepts of Zhang's completeness, the notions are discussed as extensions of interior and closure operators in a sense as Pawlak's the rough set theory. It is shown that interior operators are meet preserving maps and closure operators are join preserving maps in the perspective of Zhang's definition.

전문가 시스템에서 러프 집합을 이용한 지식 감축 (Knowledge Ruduct using Rough Set in Expert System)

  • 김두완;정환묵
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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    • pp.37-40
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    • 2001
  • 본 논문에서는 전문가 시스템에서 지식에 대한 규칙을 감소시키기 위해 러프 집합을 이용한 지식 감축 방법을 제안한다. 또한, 속성 항을 클래스로 분류하여 각 클래스와 이웃하는 클래스의 항들을 비교하여 리덕트와 코어를 구하여 최소화하였다. 이러한 방법은 방대한 양의 규칙을 최소화함으로써 의사결정 시간을 단축시킬 수 있다.

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수학적 대상으로서 ‘애매모호’ 에 대한 고찰

  • 박창균
    • 한국수학사학회지
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    • 제14권2호
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    • pp.93-100
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    • 2001
  • The problem of vagueness has been investigated for a long time by philosophers and mathematicians. There are there approaches in mathematics to the problem, which are probability theory, fuzzy logic, and rough set theory. In this paper I introduce these theories and their meanings.

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