• Title/Summary/Keyword: 군집분석법

Search Result 358, Processing Time 0.03 seconds

Charaterization of Cities in Seoul Metropolitan Area by Cluster Analysis (군집분석을 이용한 수도권 도시의 유형화에 관한 연구)

  • Song, Min-Kyung;Chang, Hoon
    • Journal of Korean Society for Geospatial Information Science
    • /
    • v.18 no.1
    • /
    • pp.83-88
    • /
    • 2010
  • This paper has analyzed Seoul metropolitan area on the basis of cluster characteristics and it is to understand the traits of each clusters. In order to modelize the area, 10 different indicators were selected among components of a city such as population, activities, land and facilities. Also through principal component analysis, similar characteristics or congenialities of the variables were derived as a common factor. The result was organized by factor score from hierarchical clustering method and as a final result, metropolitan area was clustered into five areas.

A Comparison of Cluster Analyses and Clustering of Sensory Data on Hanwoo Bulls (군집분석 비교 및 한우 관능평가데이터 군집화)

  • Kim, Jae-Hee;Ko, Yoon-Sil
    • The Korean Journal of Applied Statistics
    • /
    • v.22 no.4
    • /
    • pp.745-758
    • /
    • 2009
  • Cluster analysis is the automated search for groups of related observations in a data set. To group the observations into clusters many techniques has been proposed, and a variety measures aimed at validating the results of a cluster analysis have been suggested. In this paper, we compare complete linkage, Ward's method, K-means and model-based clustering and compute validity measures such as connectivity, Dunn Index and silhouette with simulated data from multivariate distributions. We also select a clustering algorithm and determine the number of clusters of Korean consumers based on Korean consumers' palatability scores for Hanwoo bull in BBQ cooking method.

Gene Screening and Clustering of Yeast Microarray Gene Expression Data (효모 마이크로어레이 유전자 발현 데이터에 대한 유전자 선별 및 군집분석)

  • Lee, Kyung-A;Kim, Tae-Houn;Kim, Jae-Hee
    • The Korean Journal of Applied Statistics
    • /
    • v.24 no.6
    • /
    • pp.1077-1094
    • /
    • 2011
  • We accomplish clustering analyses for yeast cell cycle microarray expression data. To reflect the characteristics of a time-course data, we screen the genes using the test statistics with Fourier coefficients applying a FDR procedure. We compare the results done by model-based clustering, K-means, PAM, SOM, hierarchical Ward method and Fuzzy method with the yeast data. As the validity measure for clustering results, connectivity, Dunn index and silhouette values are computed and compared. A biological interpretation with GO analysis is also included.

Hierarchical Clustering Analysis of Water Main Leak Location Data (상수관로 누수위치 자료를 이용한 계층적 군집분석)

  • Park, Su-Wan;Im, Gwang-Chae;Choi, Chang-Lok;Kim, Kyu-Lee
    • Journal of Korea Water Resources Association
    • /
    • v.42 no.3
    • /
    • pp.177-190
    • /
    • 2009
  • Rehabilitation projects for old water mains typically require considerable capital investments. One of the economical ways of pursuing the rehabilitation projects is to focus on a specific area within the entire region under management. In this paper the hierarchical clustering methods that analyze spatial inter-relationship of location data are applied to about 8,000 water leak location data recorded in a case study area from 1992 to 1997. Among the hierarchical clustering methods Single, Complete, and Average Linkage Methods are used to identify clusters of the water leak locations and to divide the area according to the defined clusters. By comparing the clusters identified by the clustering methods, the best clustering method for the case study area is suggested. Prioritization of the area for maintenance is obtained based on the water leak incident intensity for the clustered area using the suggested best clustering method.

Study of Rainfall Quantile Estimation using Cluster Analysis and Regional Frequency Analysis (군집분석과 지역빈도해석을 이용한 확률강우량 추정에 대한 연구)

  • Jung, Young-Hun;Jeong, Chang-Sam;Nam, Woo-Sung;Heo, Jun-Haeng
    • Proceedings of the Korea Water Resources Association Conference
    • /
    • 2010.05a
    • /
    • pp.288-291
    • /
    • 2010
  • 본 연구에서는 한강유역 109개 지점의 강우관측소에서 관측된 지속기간별 연최대강우량을 산정하고 지역빈도해석을 적용하기 위하여 한강유역에 대하여 지역구분을 실시하였다. 지역구분은 군집분석 방법인 Ward 방법, 평균연결법, Fuzzy-c means 방법, Two-Step 방법을 적용하였으며 군집분석을 수행하기 위해서 한강유역의 지점별 기상학적 인자와 지형학적 인자를 이용하여 군집분석을 수행하였다. 그 중 Fuzzy-c means 방법을 이용한 지역구분이 적합한 것으로 나타났다. 또한 모든 지속기간에 대하여 적합성 척도를 산정한 결과 GLO 분포형이 적정분포형으로 나타났으며, 지역빈도해석 방법인 지수홍수법을 이용하여 산정한 확률강우량과 지점빈도해석으로 산정한 확률강우량과 비교하여 적용성을 판단하였다.

  • PDF

붓스트랩방법의 실제적활용1) -군집표본추출법에 근거한 분할표분석을 중심으로

  • 전명식
    • Communications for Statistical Applications and Methods
    • /
    • v.3 no.1
    • /
    • pp.179-188
    • /
    • 1996
  • 복합조사표본추출법(complex survey sampling)에 근거한 분할표분석에 카이제곱검정법을 사용할 때의 문제점들과 해결방법들을 살펴보았다. 나아가, 군집표본추출의 경우에 붓스트랩방법의 타당성을 보였으며, 실제자료분석을 통하여 실제 활용가능성과 잇점을 제시하였다.

  • PDF

Simulation of the Degradation Detecting Signal Using Pattern Analysis Method (패턴 분석법을 이용한 열화 검출 신호 시뮬레이션)

  • Park, Geon-Ho
    • Proceedings of the Korean Society of Computer Information Conference
    • /
    • 2013.07a
    • /
    • pp.341-342
    • /
    • 2013
  • 본 연구에서는 배전선로의 내부 부식을 진단하는 방법이 미흡하여 예기치 못한 사고가 빈번히 발생하는 현실을 감안하여 이에 대한 대책으로 와류탐상법을 이용하여 배전선로의 내부 부식 신호를 검출한 후, 와류 탐상 신호가 매우 민감한 신호임을 고려하여 내부 부식에 대한 보다 정확한 분석을 할 수 있도록 패턴 해석 방법인 군집화기법을 이용하여 와류 탐상 신호에 대한 시뮬레이션을 수행하였으며, 배전선로의 열화 정도를 제시하기 위해 물성 변화 및 인장력을 각각 조사하였다.

  • PDF

Exploration of Hierarchical Techniques for Clustering Korean Author Names (한글 저자명 군집화를 위한 계층적 기법 비교)

  • Kang, In-Su
    • Journal of Information Management
    • /
    • v.40 no.2
    • /
    • pp.95-115
    • /
    • 2009
  • Author resolution is to disambiguate same-name author occurrences into real individuals. For this, pair-wise author similarities are computed for author name entities, and then clustering is performed. So far, many studies have employed hierarchical clustering techniques for author disambiguation. However, various hierarchical clustering methods have not been sufficiently investigated. This study covers an empirical evaluation and analysis of hierarchical clustering applied to Korean author resolution, using multiple distance functions such as Dice coefficient, Cosine similarity, Euclidean distance, Jaccard coefficient, Pearson correlation coefficient.

Bayesian analysis of finite mixture model with cluster-specific random effects (군집 특정 변량효과를 포함한 유한 혼합 모형의 베이지안 분석)

  • Lee, Hyejin;Kyung, Minjung
    • The Korean Journal of Applied Statistics
    • /
    • v.30 no.1
    • /
    • pp.57-68
    • /
    • 2017
  • Clustering algorithms attempt to find a partition of a finite set of objects in to a potentially predetermined number of nonempty subsets. Gibbs sampling of a normal mixture of linear mixed regressions with a Dirichlet prior distribution calculates posterior probabilities when the number of clusters was known. Our approach provides simultaneous partitioning and parameter estimation with the computation of classification probabilities. A Monte Carlo study of curve estimation results showed that the model was useful for function estimation. Examples are given to show how these models perform on real data.

The Characteristics of Korean Family Law - A Comparison with EU-Countries in Regard to Regime Classification - (한국 가족법의 특수성 - EU 국가와의 비교를 통한 유형 구분 -)

  • Chung, Yun Tag
    • Korean Journal of Social Welfare Studies
    • /
    • v.41 no.4
    • /
    • pp.161-187
    • /
    • 2010
  • This study begins with two research interests. Firstly, there seems to be a break of research in the field of family policy in Korea which exists especially in regard to family law. Family law was originally the core of state interventions in family life, but has been neglected because of the lack of literature with comparative research methods. This shortcoming needs to be addressed. Secondly, through inquiry into the definition of family or family policy with the lens of the law, the definition of family or family policy can be correctly extended. With these two interests combined, this research tries to derive an analytical tool - maintenance community - of the law and compare some important points of the family law of Korea with those of 16 EU-countries in terms of regime classification. The method used is, firstly, to describe the subjects of family law with a focus on partnering and parenting without subjective interpretation, and secondly, to classify the countries' family-law regimes with the criteria of privacy and autonomy using cluster analysis. The results show that the countries can be classified into three clusters: Nordic (Norway and Sweden), West-Northern (Denmark, France, England, Finland, and Belgium) and Middle South (Italy, Spain, Austria, Portugal, Netherlands, Greece, Ireland, Germany, and Korea). This result can be compared to a precedent research result which showed that 21 OECD countries can be classified in three clusters according to family policy. The number of the clusters is the same as this study, but some countries belong to other clusters; for example Denmark and Finland belong to the Nordic cluster according to family policy, while they belong to the West-Northern according to family law, and Austria, Germany, and Ireland belong to the Middle-South cluster according to family law, while they belong to the Continental according to family policy. From this result we can interpret Korean family law to be in the middle range according to both criteria of privacy and autonomy like other South-European countries including some Continental countries. We can make some theoretical suggestions. The fact that both family law and family policy regimes in countries can be classified into three clusters can be interpreted to mean that there exists parallelism between family law and family policy in a broad sense. But from the fact that some countries belong to different clusters according to family law and family policy, we can say that the family policy in a country is not always consistent with family law.