• Journal of Korean Society of Coastal and Ocean Engineers
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• v.21 no.3
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• pp.254-265
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• 2009

The estimation of the extreme sea level is necessary in the design of offshore or coastal structures. In this paper, the storm surge data calculated numerically at 52 harbors around the Korean Peninsula are analyzed by using annual maximum series(AMS), peaks over threshold(POT) and empirical simulation technique(EST). The maximum likelihood method was used to estimate the parameters in both AMS and POT models. The Generalized Pareto distribution was used and Chi-square and Kolmogorov-Smirnov goodness-of-fit tests were performed with the acceptable significance level 5%. The extreme sea levels were also evaluated by EST including tide effect, showing similar results as given by Jeong et al.(2008).

• Journal of the Korean Society for Railway
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• v.14 no.5
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• pp.470-476
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• 2011

This study proposed the intervention ARIMA model as a way to forecast the KTX passenger demand. The second phase of the Gyeongbu high-speed rail project and the financial crisis in 2008 were analyzed in order to determine the effect of time series on the opening of a new line and economic impact. As a result, the financial crisis showed that there is no statistically significant impact, but the second phase of the Gyeongbu high-speed rail project showed that the weekday trips increased about 17,000 trips/day and the weekend trips increased about 26,000 trips/day. This study is meaningful in that the intervention explained the phenomena affecting the time series of KTX trip and analyzed the impact on intervention of time series quantitatively. The developed model can be used to forecast the outline of the overall KTX demand and to validate the KTX O/D forecasting demand.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.987-998
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• 2013

This paper considers the statistical characteristics on the air quality (PM10) of Korea collected hourly in 2011. PM10 in Korea exhibits very strong correlations even for higher lags, namely, long range dependence. It is power-law tailed in marginal distribution, and generalized Pareto distribution successfully captures the thicker tail than log-normal distribution. However, slowly decaying autocorrelations may confuse practitioners since a non-stationary model (such as changes in mean) can produce spurious long term correlations for finite samples. We conduct a statistical testing procedure to distinguish two models and argue that the high persistency can be explained by non-stationary changes in mean model rather than long range dependent time series models.

• The Journal of the Korea Contents Association
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• v.16 no.12
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• pp.735-748
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• 2016

Since the number of student is regarded as the fundamental basis to calculate the future allocation of employed teachers, it needs to be systematically estimated based on statistical data. In order to achieve this purpose, the number of high school students is projected following the assumption that the teacher-student ratio of Korea should be adjusted to the level of OECD to improve the quality of education. Hence, this paper introduced the projection methods by time series model. To predict the number of high school students and error estimation, various models were adopted.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.395-406
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• 2017

The purpose of this study is to identify the pattern of daily electricity demand through clustering and classification. The hourly data was collected by KPS (Korea Power Exchange) between 2008 and 2012. The time trend was eliminated for conducting the pattern of daily electricity demand because electricity demand data is times series data. We have considered k-means clustering, Gaussian mixture model clustering, and functional clustering in order to find the optimal clustering method. The classification analysis was conducted to understand the relationship between external factors, day of the week, holiday, and weather. Data was divided into training data and test data. Training data consisted of external factors and clustered number between 2008 and 2011. Test data was daily data of external factors in 2012. Decision tree, random forest, Support vector machine, and Naive Bayes were used. As a result, Gaussian model based clustering and random forest showed the best prediction performance when the number of cluster was 8.

• Spatial Information Research
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• v.19 no.1
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• pp.29-40
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• 2011

GOCI the world first Ocean Color Imager in Geostationary Orbit, which could obtain total 8 images of the same region a day, however, its spatial resolution(500m) is not enough to use for the accurate land application, Super Resolution(SR), reconstructing the high resolution(HR) image from multiple low resolution(LR) images introduced by computer vision field. could be applied to the time-series remotely sensed images such as GOCI data, and the higher resolution image could be reconstructed from multiple images by the SR, and also the cloud masked area of images could be recovered. As the precedent study for developing the efficient SR method for GOCI images, on this research, it reproduced the simulated data under the acquisition process of the remote sensed data, and then the simulated images arc applied to the proposed algorithm. From the proposed algorithm result of the simulated data, it turned out that low resolution(LR) images could be registered in sub-pixel accuracy, and the reconstructed HR image including RMSE, PSNR, SSIM Index value compared with original HR image were 0.5763, 52.9183 db, 0.9486, could be obtained.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2
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• pp.58-65
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• 1997

A new automatic classification method with high and stable accuracy for time-series image data is presented in this paper. This method is based on prior condition that a classified map of the target area already exists, or at least one of the time-series image data had been classified. The classified map is used as a reference map to specify training areas of classification categories. The new automatic classification method consists of five steps, i.e., extraction of training data using reference map, detection of changed pixels based upon the homogeneity of training data, clustering of changed pixels, reconstruction of training data, and classification as like maximum likelihood classifier. In order to evaluate the performance of this method qualitatively, four time-series Landsat TM image data were classified by using this method and a conventional method which needs a skilled operator. As a results, we could get classified maps with high reliability and fast throughput, without a skilled operator.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.467-471
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• 2010

유속지수법(index velocity method)은 수위-유량관계에 유속을 추가적인 지수로 이용하는 방법이며 현재 자동유량측정 방법으로 널리 사용되고 있는 기법이다. 유속지수법에 많이 사용되는 측정 장비는 초음파유량계와 Acoustic Doppler Velocity Meter(ADVM) 등으로 모두 연속적인 수위와 유속을 측정하여 시계열 유량 자료를 생산하기 때문에 고리형 수위-유량관계의 재현이 가능하다. 기존의 연구에서 유속지수법은 괴산댐 하류에 적용되어 댐 방류량대비 평균 7%의 상대오차를 보였고, 시간에 따른 오차 발생이 적어 수위-유량관계에 비해 효율적으로 나타났다. 하지만 댐방류량에 의해 영향받는 구간에서는 고리형 수위-유량관계 재현에 한계를 나타냈다. 따라서 본 연구에서는 일반 자연하천인 임진강 적성지점에 ADVM을 설치하였고, 수위-단면적 관계와 평균유속($V_m$)-지표유속($V_i$) 관계를 수립하여 유속지수법에 의한 시계열 유량자료를 산정하였다. 산정된 유량자료는 측정 유량과 비교하여 정확도를 분석하였고, 시계열 유량 자료로부터 고리형 수위-유량관계를 재현하였다. 2009년 6월부터 9월까지 운영된 ADVM 자료로부터 산정된 유속지수법 최대 유량은 $10,491m^3/s$였으며, 총 18회의 실측 유량과 비교한 유속지수법 유량은 평균 7%의 상대오차를 나타냈다. 시계열 자료로부터 재현된 고리형 수위-유량관계는 임진강 적성지점의 경우 수위관측소 수위 10m, 유량 $2,000m^3/s$부터 발생하였다. 2009년 8월 11일 첨두유량 $8,000m^3/s$홍수 사상에서 발생한 고리형 수위-유량관계의 경우 수위 14m에서 $1,230m^3/s$의 유량차이를 보였고, 동일한 유량 $6,000m^3/s$에서 1.2m의 수위차이를 보였다. 2009년 8월 26일 첨두유량 $10,000m^3/s$에서 발생한 고리형 수위-유량관계에서도 마찬가지로 수위 16m에서 $1,670m^3/s$의 유량차, 유량 $8,000m^3/s$에서 수위 1.3m의 차이를 나타냈다. 이와 같이 유속지수법은 기존의 수위-유량관계가 가지는 한계점을 보완하여 고리형 수위-유량관계 재현이 가능하기 때문에 보다 정확한 유량 산정이 가능할 것으로 판단된다.

• The KIPS Transactions:PartD
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• v.15D no.1
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• pp.31-40
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• 2008

We generally use lower-dimensional transformations to convert high-dimensional sequences into low-dimensional points in similar sequence matching. These traditional transformations, however, show different characteristics in indexing performance by the type of time-series data. It means that the selection of lower-dimensional transformations makes a significant influence on the indexing performance in similar sequence matching. To solve this problem, in this paper we propose a hybrid approach that integrates multiple transformations and uses them in a single multidimensional index. We first propose a new notion of hybrid lower-dimensional transformation that exploits different lower-dimensional transformations for a sequence. We next define the hybrid distance to compute the distance between the transformed sequences. We then formally prove that the hybrid approach performs the similar sequence matching correctly. We also present the index building and the similar sequence matching algorithms that use the hybrid approach. Experimental results for various time-series data sets show that our hybrid approach outperforms the single transformation-based approach. These results indicate that the hybrid approach can be widely used for various time-series data with different characteristics.

• KIISE Transactions on Computing Practices
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• v.22 no.5
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• pp.201-208
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• 2016

Collection and storing of multiple time series data in real time requires large memory space. To solve this problem, the usage of varying sample size is proposed in the compression scheme using discrete cosine transform technique. Time series data set has characteristics such that a higher compression ratio can be achieved with smaller amount of value changes and lower frequency of the value changes. The coefficient of variation and the variability of the differences between adjacent data elements (VDAD) are presumed to be very good measures to represent the characteristics of the time series data and used as key parameters to determine the varying sample size. Test results showed that both VDAD-based and the coefficient of variation-based scheme generate excellent compression ratios. However, the former scheme uses much simpler sample size decision mechanism and results in better compression performance than the latter scheme.