• 제목/요약/키워드: Principal Components

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주성분 분석법을 이용한 시군단위별 농업가뭄에 대한 취약성 분석에 관한 연구 - 경기도를 중심으로 - (County-Based Vulnerability Evaluation to Agricultural Drought Using Principal Component Analysis - The case of Gyeonggi-do -)

  • 장민원
    • 농촌계획
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    • 제12권1호
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    • pp.37-48
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    • 2006
  • The objectives of this study were to develop an evaluation method of regional vulnerability to agricultural drought and to classify the vulnerability patterns. In order to test the method, 24 city or county areas of Gyeonggi-do were chose. First, statistic data and digital maps referred for agricultural drought were defined, and the input data of 31 items were set up from 5 categories: land use factor, water resource factor, climate factor, topographic and soil factor, and agricultural production foundation factor. Second, for simplification of the factors, principal component analysis was carried out, and eventually 4 principal components which explain about 80.8% of total variance were extracted. Each of the principal components was explained into the vulnerability components of scale factor, geographical factor, weather factor and agricultural production foundation factor. Next, DVIP (Drought Vulnerability Index for Paddy), was calculated using factor scores from principal components. Last, by means of statistical cluster analysis on the DVIP, the study area was classified as 5 patterns from A to E. The cluster A corresponds to the area where the agricultural industry is insignificant and the agricultural foundation is little equipped, and the cluster B includes typical agricultural areas where the cultivation areas are large but irrigation facilities are still insufficient. As for the cluster C, the corresponding areas are vulnerable to the climate change, and the D cluster applies to the area with extensive forests and high elevation farmlands. The last cluster I indicates the areas where the farmlands are small but most of them are irrigated as much.

로지스틱모형에서의 주성분회귀 (Principal Components Regression in Logistic Model)

  • 김부용;강명욱
    • 응용통계연구
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    • 제21권4호
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    • pp.571-580
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    • 2008
  • 로지스틱회귀분석은 고객관계관리나 신용위험관리 등의 분야에서 많이 사용되는 기법인데, 이러한 분야에서의 로지스틱회귀모형에는 연관성이 높은 설명변수들이 다수 포함되어 다중공선성의 문제를 유발하는 경우가 있다. 다중공선성이 존재하는 상황에서 최우추정량은 심각한 결함을 갖는다는 사실은 잘 알려졌다. 이 문제를 해결하기 위하여 로지스틱주성분회귀를 연구하되, 분석상의 주요 과정인 주성분 선정을 위한 방법을 새롭게 제안하였다. 추정량의 분산을 최소가 되게 하는 상태지수 값을 측정하고, 이 값에 영향을 미치는 주요 요인들을 컨조인트분석에 의해 파악하여 주성분 선정기준을 결정하는 모형을 구축하였다. 제안된 방법은 다중공선성 문제를 적절히 해결하면서도 모형의 적합성을 향상시킨다는 사실이 모의실험을 통하여 확인되었다.

Arrow Diagrams for Kernel Principal Component Analysis

  • Huh, Myung-Hoe
    • Communications for Statistical Applications and Methods
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    • 제20권3호
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    • pp.175-184
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    • 2013
  • Kernel principal component analysis(PCA) maps observations in nonlinear feature space to a reduced dimensional plane of principal components. We do not need to specify the feature space explicitly because the procedure uses the kernel trick. In this paper, we propose a graphical scheme to represent variables in the kernel principal component analysis. In addition, we propose an index for individual variables to measure the importance in the principal component plane.

TM 유형 중국식 레스토랑의 전통성 표현 특성 연구 - 홍콩에 소재한 레스토랑을 중심으로 - (A Study on the Characteristics of Traditionality Expression at TM Style Chinese Restaurants - Focused on Chinese Restaurants in Hong kong -)

  • 김지은;오혜경
    • 한국실내디자인학회논문집
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    • 제21권5호
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    • pp.280-288
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    • 2012
  • The objective of this study was to analyze the characteristics of traditionality expressions at modernized Chinese restaurant in Hong Kong. As a case study, the study examined 12 modernized Chinese restaurants in Hong Kong. The gathered data were categorized and examined according to the ways of traditionality expressions, which included reproduction, transformation, and reinterpretation of traditional components. Each of the components was measured for the amount of traditional or modernity expression on a five-point scale. The five-point scoring system put an emphasis on tradition; 1 point was given to principal modernity(modernity: 90-100% + tradition: 0-10%), 2 points were given to principal modernity + auxiliary tradition(modernity: 70-90% + tradition: 10-30%), 3 points were given to the same ratio between tradition and modernity(modernity: 40-60% + tradition: 40-60%), 4 points were given to principal tradition + auxiliary modernity(modernity: 10-30% + tradition: 70-90%), and 5 points were given to principal tradition(modernity: 0-10% + tradition: 90-100%). The analysis performed according to those criteria and methodologies led to the following findings and conclusions: TM style, in which modernity was principal, usually did transformation and reinterpretation of traditionality. As for the design attributes of the styles, the TM style, they processed a majority of the spatial components as modern or reinterpretation of traditionality, which would be easily considered to be modern without careful observation, and applied a small amount of direct reproduction or transformation, which gives out a direct hint at traditionality, to attract more attention. Many of the spatial components did not express traditionality directly, expressing it indirectly or metaphorically. Traditionality was expressed in a small number of the spatial components, thus serving as a focus or impact point in the given space.

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SKL 알고리즘을 이용한 얼굴인식 후보의 점진적 등록 (Sequential Registration of the Face Recognition candidate using SKL Algorithm)

  • 한학용;이생목;곽부동;최원태;강봉순
    • 융합신호처리학회논문지
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    • 제11권4호
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    • pp.320-325
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    • 2010
  • 본 논문은 주성분 분석을 이용하는 얼굴인식 시스템에서 인식후보를 점진적으로 등록하기 위한 방법과 절차에 관한 연구이다. 점진적인 주성분 갱신 방법으로 R-SVD알고리즘을 변형한 SKL 알고리즘을 이용한다. SKL 알고리즘을 이용하면 주성분을 이용하는 얼굴 인식의 문제점으로 지적되어 왔던 인식 후보의 점진적 증가에 따른 재학습 문제를 해결할 수 있다. 또한 이 방법은 밝기 변화에 견고한 객체 트랙킹 분야에도 이용될 수 있다. 본 논문에서는 얼굴인식 시스템에서 SKL 알고리즘을 이용하여 주성분을 점진적으로 갱신하며 적용하는 절차를 제안하고, 표준 KL 변환에 의하여 주성분을 일괄적으로 계산하는 결과와 얼굴 인식성능을 비교한다. 그리고 SKL 알고리즘에 포함된 망각 인자(forgetting factor)가 얼굴인식 성능에 미치는 효과를 실험적으로 확인한다.

통계분석을 이용한 소규모 유역내 하천수 수질과 지질과의 상관관계 해석

  • 고경석;김재곤;이진수;김용제;조춘희
    • 한국지하수토양환경학회:학술대회논문집
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    • 한국지하수토양환경학회 2004년도 총회 및 춘계학술발표회
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    • pp.311-314
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    • 2004
  • To identify the effect of geology and land use, the hydrogeochemical and multivariate statitstical analysis were executed for stream water collected in headwater region of Daecheong reservoir. Hydrogeochemical analysis was showed the effect of weathering process such as dissolution of calc-silicate minerals to hydrochemistry of stream water with contrasting geology. Cluster and principal components analysis can also help to identify the source of dissolved components in stream water.

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Interpretation of Agronomic Traits Variation of Sesame Cultivar Using Principal Component Analysis

  • Shim, Kang-Bo;Hwang, Chung-Dong;Pae, Suk-Bok;Park, Jang-Whan;Byun, Jae-Cheon;Park, Keum-Yong
    • 한국작물학회지
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    • 제54권1호
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    • pp.24-28
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    • 2009
  • This study was conducted to evaluate the growth characters and yield components of 18 collected sesame cultivars to get basic information on the variation for the sesame breeding using principal component analysis. All characters except days to flowering, days to maturity and 1,000 seed weight showed significantly different. Seed weight per 10 are showed higher coefficient of variance. Capsule bearing stem length and liter weight showed positive correlation with seed yield per 10 are. The principal components analysis grouped the estimated sesame cultivars into four main components which accounted for 83.7% of the total variation at the eigenvalue and its contribution to total variation obtained from principal component analysis. The first principal component ($Z_1$) was applicable to increase plant height, capsule bearing stem length and 1,000-seed weight. The second principal component ($Z_2$) negatively correlated with days to flowering and maturity by which it was applicable to shorten flowering and maturity date of sesame. At the scatter diagram, Yangbaek, Ansan, M1, M2, M4, M7 and M9 were classified as same group, but M10, Yanghuk, Kanghuk, M5, M6, M12 and M13 were classified as different group. This results would be helpful for sesame breeder to understand genetic relationship of some agronomic characters and select promising cross lines for the development of new sesame variety.

Asymptotic Test for Dimensionality in Probabilistic Principal Component Analysis with Missing Values

  • Park, Chong-sun
    • Communications for Statistical Applications and Methods
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    • 제11권1호
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    • pp.49-58
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    • 2004
  • In this talk we proposed an asymptotic test for dimensionality in the latent variable model for probabilistic principal component analysis with missing values at random. Proposed algorithm is a sequential likelihood ratio test for an appropriate Normal latent variable model for the principal component analysis. Modified EM-algorithm is used to find MLE for the model parameters. Results from simulations and real data sets give us promising evidences that the proposed method is useful in finding necessary number of components in the principal component analysis with missing values at random.

주성분 분석을 이용한 HRIR 맞춤 기법 (HRIR Customization in the Median Plane via Principal Components Analysis)

  • 황성목;박영진
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2007년도 춘계학술대회논문집
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    • pp.120-126
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    • 2007
  • A principal components analysis of the entire median HRIRs in the CIPIC HRTF database reveals that the individual HRIRs can be adequately reconstructed by a linear combination of several orthonormal basis functions. The basis functions cover the inter-individual and inter-elevation variations in median HRIRs. There are elevation-dependent tendencies in the weights of basis functions, and the basis functions can be ordered according to the magnitude of standard deviation of the weights at each elevation. We propose a HRIR customization method via tuning of the weights of 3 dominant basis functions corresponding to the 3 largest standard deviations at each elevation. Subjective listening test results show that both front-back reversal and vertical perception can be improved with the customized HRIRs.

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Metabolic Discrimination of Safflower Petals of Various Origins Using 1H NMR Spectroscopy and Multivariate Statistical Analysis

  • Whang, Wan-Kyun;Lee, Min-Won;Choi, Hyung-Kyoon
    • Bulletin of the Korean Chemical Society
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    • 제28권4호
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    • pp.557-560
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    • 2007
  • The metabolic discrimination of safflowers from various geographical origins was performed using 1H nuclear magnetic resonance (NMR) spectroscopy followed by principal components analysis. With a combination of these techniques, safflower samples from different origins could be discriminated using the first two principal components (PC) of the 1H NMR spectra of the 50% methanol fractions. PC1 and PC2 accounted cumulatively for 91.3% of the variation in all variables. The major peaks in the 1H NMR spectra that contributed to the discrimination were assigned to fatty acid (terminal CH3), lactic acid, acetic acid, choline derivatives, glycine, and safflower yellow derivatives. In this study, we suggest that various types of safflower can be discriminated using PCA and 1H NMR spectra.