• Journal of Korea Port Economic Association
• /
• v.34 no.3
• /
• pp.17-52
• /
• 2018

The purpose of this paper is to measure the clustering change and analyze empirical results. Additionally, by using k-means, hierarchical, and mixed models on Asian container ports over the period 2006-2015, the study aims to form a cluster comprising Busan, Incheon, and Gwangyang ports. The models consider the number of cranes, depth, birth length, and total area as inputs and container twenty-foot equivalent units(TEU) as output. Following are the main empirical results. First, ranking order according to the increasing ratio during the 10 years analysis shows that the value for average linkage(AL), mixed ward, rule of thumb(RT)& elbow, ward, and mixed AL are 42.04% up, 35.01% up, 30.47%up, and 23.65% up, respectively. Second, according to the RT and elbow models, the three Korean ports can be clustered with Asian ports in the following manner: Busan Port(Hong Kong, Guangzhou, Qingdao, and Singapore), Incheon Port(Tokyo, Nagoya, Osaka, Manila, and Bangkok), and Gwangyang Port(Gungzhou, Ningbo, Qingdao, and Kasiung). Third, optimal clustering numbers are as follows: AL(6), Mixed Ward(5), RT&elbow(4), Ward(5), and Mixed AL(6). Fourth, empirical clustering results match with those of questionnaire-Busan Port(80%), Incheon Port(17%), and Gwangyang Port(50%). The policy implication is that related parties of Korean seaports should introduce port improvement plans like the benchmarking of clustered seaports.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2010.05a
• /
• pp.1429-1433
• /
• 2010

수공구조물의 설계, 수자원 관리계획의 수립, 재해영향 검토 등을 수행할 때, 재현기간에 따른 확률개념의 강우량, 홍수량, 저수량 등을 산정하여 사용하게 되며, 보통 대상지역의 장기 수문관측 자료를 이용하여 수문사상의 확률분포를 산정한 후 재현기간을 연장하여 원하는 설계빈도에 해당하는 양을 추정하게 된다. 미계측지역 또는 관측자료의 보유기간이 짧은 지역의 경우는 지역빈도 분석 결과를 이용하게 된다. 지역빈도해석을 위해서는 강우자료들의 동질성을 파악하는 것이 가장 기본적인 과정이 되며 이를 위해 통계학적인 범주화분석이 선행되어야 한다. 지점 빈도분석의 수문학적 동질성 판별을 위해 L-moment 방법, K-means 방법에 의한 군집분석 등이 주로 사용되며 관측소 위치좌표를 이용한 공간보간법을 적용하여 시각화하고 있다. 강수량은 시공간적으로 변하는 수문변량으로서 강수량의 시간적인 특성 또한 강수량의 특성을 정의하는데 매우 중요한 요소이다. 이러한 점에서 본 연구를 통해 강수지점의 공간적인 좌표 및 강수량의 양적인 범주화에 초점을 맞춘 기존 지역빈도분석의 범주화 과정에 덧붙여 시간적인 영향을 고려할 수 있는 요소들을 결정하고 이를 활용할 수 있는 범주화 과정을 제시하고자 한다. 즉, 극치강수량의 발생 시기에 대한 정량적인 분석이 가능한 순환통계기법을 이용하여 관측 지점별 시간 통계량을 산정하고, 이를 극치강수량과 결합하여 시 공간적인 특성자료를 생성한 후 이를 이용한 군집화 해석 모형을 개발하는데 연구의 목적이 있다. 분석 과정에 있어서 시간속성의 정량화 및 일반화는 순환통계기법을 사용하였으며, 극치강수량과 발생시점의 속성자료는 각각의 평균과 표준편차를 이용하였다. K-means 알고리즘을 이용해 결합자료를 군집화 하고, L-moment 방법으로 지역화 결과에 대한 검증을 수행하였다. 속성 결합 자료의 군집화 효과는 모의데이터 실험을 통해 확인하였으며, 우리 나라의 58개 기상관측소 자료를 이용하여 분석을 수행하였다. 예비해석 단계에서 100회의 군집분석을 통해 평균적인 centroid를 산정하고, 해당 값을 본 해석의 초기 centroid로 지정하여, 변동적인 클러스터링 경향을 안정화시켜 해석이 반복됨에 따라 군집화 결과가 달라지는 오류를 방지하였다. 또한 K-means 방법으로 계산된 군집별 공간거리 합의 크기에 따라 군집번호를 부여함으로써 군집의 번호순서대로 물리적인 연관성이 인접하도록 설정하였으며, 군집간의 경계선을 추출할 때 발생할 수 있는 오류를 방지하였다. 지역빈도분석 결과는 3차원 Spline 기법으로 도시하였다.

• Journal of the Korean earth science society
• /
• v.33 no.4
• /
• pp.337-349
• /
• 2012

In this study, we classify the 1000 hPa geopotential height fields around the Korean peninsula through the Kmeans cluster analysis and investigate the occurrence characteristics of each cluster pattern. The 11 clusters are identified as the typical pressure patterns, applying the pattern correlation as a similarity among clusters and the criterion of cluster similarity 0.8, of which three pressure patterns are associated with the extension of Siberia air mass, other three with the latitudes of the longest symmetry axis of North Pacific highs, two with the trough largely under the air mass of Siberia or North Pacific, and the remaining three, the migratory high patterns generally occurring in spring and autumn, are disjointed according to the direction of the longest symmetry axis of highs. The occurrence rate of air masses affecting the Korean peninsula, estimated from the number of occurrence days of 11 pressure patterns, is 55.4% Siberian, 29.3% North Pacific, 12.8% Yangtze-River, 2.5% Okhotsk sea and 68.2% of all these is the continental air masses. The wintertime pressure patterns around the Korean peninsula are nearly contrary to those in summertime, each dominated by the highs extended from the stationary air masses over the Central Siberia and the North Pacific ocean. The migratory highs occur largely in spring and autumn while transferring from the wintertime patterns to summertime patterns, or vice versa. Recently, the occurrence frequency of the highs extended from the North Pacific is on the decrease and while the wintertime pressure patterns occur frequently in spring and autumn, the occurrence frequency of the pressure patterns with trough is on the increase and the migratory highs occur in nearly all seasons.

• Journal of the Korean Geographical Society
• /
• v.44 no.1
• /
• pp.1-16
• /
• 2009

This study aims to classify climate zones using Empirical Orthogonal Function and clustering analyses considering both air temperature and rainfall features in South Korea. When examining climatic characteristics of air temperature and rainfall by seasons, the distribution of air temperature is affected by topography and latitude for all seasons in South Korea. The distribution of rainfall demonstrated that the Yeongdong area, the southern coastal area and Jeju island have higher rainfall while the central area in Gyeongsangbuk-do is the least rainfall area. Clustering analyses of average linkage method and Ward's method was carried out using input variables derived from principal component scores calculated through Empirical Orthogonal Function analysis for air temperature and rainfall. Ward's method showed the best result of classification of climate zones. It was well reflected effects of topography, latitude, sea, the movement of surface pressure systems, and an administrative district.

• Korean Journal of Ecology and Environment
• /
• v.38 no.2 s.112
• /
• pp.188-195
• /
• 2005

The dynamics of the fish community in the Lake Hoengseong region, Korea, were investigated from April 2000 to November 2004. During the surveyed period 39 species belonging 10 families were collected, and there were 17 Korean endemic species (43.59%) including Rhodeus pseudosericeus. Dominant species were Acheilognathus lanceolatus (20.10%), Zacco platypus (15.94%), Z. temmincki (6.92%), Carassius cuvieri (6.33%), A. rhombeus (6.18%), Pungtungia herzi (5.13%), and Pseudorasbora parva (4.93), In the comparison community of fish according to ecotype by each studied years, benthic fished are gradually decreasing and pelagic fishes creasing. Also, according to the fish distribution, the fish community of each studied years was divided into 3 groups by UPGMA. Being based on the fish community, similarity analysis results of each artificial lakes and this lake were divided 2 groups by water system, and divided again 3 groups in the same water system. Fish Community of the Lake Hoengseong was similar with that of the Lake Chuncheon and Cheongpyeong of the Bukhan-River.

• Korean Journal of Environment and Ecology
• /
• v.23 no.2
• /
• pp.208-219
• /
• 2009

This study is to establish a management method for conservation through comparison and analysis on vegetation structures of Pinus densiflora forest around Beopjusa area for past 17-year. The spatial range of the study was $3.6km^2$ from maintenance office to Beopjusa area. The analysis results of the actual vegetation showed that the ratio of vegetation were composed of 64.7% of Pinus densiflora forest, 3.2% of mixed forest of P. densiflora and deciduous broadleaf trees and 5.9% of deciduous broadleaf tree community out of overall area, 360ha. The type of P. densiflora forest were categorized into four communities; community having high potential of succession, community having low potential of it, the community being in the process of succession and community being in the process of natural selection. The succession tendency was in order of the community having low potential of succession(P. densiflora forest), having high potential of it(P. densiflora forest which is deciduous broadleaf trees are dominating in sub-canopy layer), being in the process of succession(P. densiflora-Prunus sargentii and P. densiflora-Quercus serrata community) and being in the process of natural selection(Q. serrata-P. densiflora and Q. aliena-P. densiflora community). In terms of vegetation management, P. densiflora forest having high potential of succession was needed to remove deciduous broadleaf trees in the sub-canopy layer and the community being in the process of succession was required to be pruning the branch in the canopy layer. Lastly, the community being in the process of natural selection was suggested to let it be in succession, since it is hard to be in the status of P. densiflora Forest.

• Journal of Korean Society for Geospatial Information Science
• /
• v.19 no.4
• /
• pp.139-144
• /
• 2011

This study proposed a classification method of LIDAR data by using simultaneously the color information (R, G, B) and reflection intensity information (I) obtained from terrestrial LIDAR and by analyzing the association between these data through the use of statistical classification methods. To this end, first, the factors that maximize variance were calculated using the variables, R, G, B, and I, whereby the factor matrix between the principal factor and each variable was calculated. However, although the factor matrix shows basic data by reducing them, it is difficult to know clearly which variables become highly associated by which factors; therefore, Varimax method from orthogonal rotation was used to obtain the factor matrix and then the factor scores were calculated. And, by using a non-hierarchical clustering method, K-mean method, a cluster analysis was performed on the factor scores obtained via K-mean method as factor analysis, and afterwards the classification accuracy of the terrestrial LiDAR data was evaluated.

• Journal of Plant Biotechnology
• /
• v.42 no.4
• /
• pp.401-408
• /
• 2015

Horticultural traits and genetic relationship were evaluated for 83 melon (Cucumis melo L.) cultivars. Survey of a total of 36 characteristics for seedling, leaf, stem, flower, fruit, and seed and subsequent multiple analysis of variance (MANOVA) were conducted. Principal component analysis (PCA) showed that 8 principle components including fruit weight, fruit length, fruit diameter, cotyledon length, seed diameter, and seed length accounted for 76.3% of the total variance. Cluster analysis of the 83 melon cultivars using average linkage method resulted in 5 clusters at coefficient of 0.7. Cluster I consisted of cultivars with high values for fruit-related traits, Cluster II for soluble solid content, and Cluster V for high ripening rate. Genotyping of the 83 cultivars was conducted using 15 expressed-sequence tagged-simple sequence repeat (EST-SSR) from the Cucurbit Genomics Initiative (ICuGI) database. Analysis of genetic relatedness by UPGMA resulted in 6 clusters. Mantel test indicated that correlation between morphological and genetic distance was very low (r = -0.11).

• 한국신재생에너지학회:학술대회논문집
• /
• 2009.06a
• /
• pp.554-556
• /
• 2009

Wind classification for exact estimation of wind energy resources was carried out using numerically simulated wind data for three years. The MM5(a fifth-generation Mesoscale Model), developed at Penn State University and the National Center for Atmospheric Research (NCAR), was used to estimate the wind fields in this study. We also use a variant of the K-mean clustering to classify the wind district and define the relation between districts. Wind estimated at surface and 100 m high at Busan area is classified into the 10 and 7 classes, respectively. These discrepancies of wind districts pattern at surface and upper air meteorological data indicates the quantity of wind resources can be changed according to the level of wind data used in estimation. Therefore, the estimation of wind district classification by reasonable wind data is utilized to build the effective policy for wind energy dissemination.

• Journal of the Economic Geographical Society of Korea
• /
• v.15 no.4
• /
• pp.615-627
• /
• 2012

This study analyzed the travel pattern with respect to use of public transportation by using transportation card data and presented the measures that can be used in a traffic policy. Transportation card data targeted Gyeonggi-Do area and as a utilization plan, a scenario that when a traffic policy decision maker improves bus stop facilities, the person selects a target site by using several variables that can be obtained from transportation card data was set and analyzed. The analysis result showed that K means cluster analysis which is decision making methodology and CHAID(Chi-squared automatic interaction detection) were used and it can be used usefully in policies in significance level of p <0.01. Also, based on these results, this study presented policy implications to be improved to actually use transportation card data in policies.