• Ocean and Polar Research
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• 제42권3호
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• pp.211-223
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• 2020

With the increasing demand for improved marine environments and safety, greater ability to minimize damages to coastal areas from harmful organisms, ship accidents, oil spills, etc. is required. In this regard, an accurate assessment and understanding of current systems is a crucial step to improve forecasting ability. In this study, we examine spatial and temporal characteristics of current systems in the adjacent seas of Jeju Island using a high-resolution regional ocean circulation model. Our model successfully captures the features of tides and tidal currents observed around Jeju Island. The tide form number calculated from the model result ranges between 0.3 and 0.45 in the adjacent seas of Jeju Island, indicating that the dominant type of tides is a combination of diurnal and semidiurnal, but predominantly semidiurnal. The spatial pattern of tidal current ellipses show that the tidal currents oscillate in a northwest-southeast direction and the rotating direction is clockwise in the adjacent seas of Jeju Island and counterclockwise in the Jeju Strait. Compared to the mean kinetic energy, the contribution of tidal current energy prevails the most parts of the region, but largely decreases in the eastern seas of Jeju Island where the Tsushima Warm Current is dominant. In addition, a Lagrangian particle-tracking experiment conducted suggests that particle trajectories in tidal currents flowing along the coast may differ substantially from the mean current direction. Thus, improving our understanding of tidal currents is essential to forecast the transport of marine pollution and harmful organisms in the adjacent seas of Jeju Island.

• 대한산업공학회지
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• 제37권1호
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• pp.64-73
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• 2011

Oil price prediction is an important issue for the regulators of the government and the related industries. When employing the time series techniques for prediction, however, it becomes difficult and challenging since the behavior of the series of oil prices is dominated by quantitatively unexplained irregular external factors, e.g., supply- or demand-side shocks, political conflicts specific to events in the Middle East, and direct or indirect influences from other global economical indices, etc. Identifying and quantifying the relationship between oil price and those external factors may provide more relevant prediction than attempting to unclose the underlying structure of the series itself. Technically, this implies the prediction is to be based on the vectoral data on the degrees of the relationship rather than the series data. This paper proposes a novel method for time series prediction of using Semi-Supervised Learning that was originally designed only for the vector types of data. First, several time series of oil prices and other economical indices are transformed into the multiple dimensional vectors by the various types of technical indicators and the diverse combination of the indicator-specific hyper-parameters. Then, to avoid the curse of dimensionality and redundancy among the dimensions, the wellknown feature extraction techniques, PCA and NLPCA, are employed. With the extracted features, a timepointspecific similarity matrix of oil prices and other economical indices is built and finally, Semi-Supervised Learning generates one-timepoint-ahead prediction. The series of crude oil prices of West Texas Intermediate (WTI) was used to verify the proposed method, and the experiments showed promising results : 0.86 of the average AUC.

• 한국수산경영학회:학술대회논문집
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• 한국수산경영학회 2007년도 춘계학술발표회 및 심포지엄
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• pp.19-41
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• 2007

In Side of Supply and Demand of Fisheries Products, The Aquacultural Industry stayed in subsidized situation for the whole fishery industry of korea when it's dawned. But nowaday, the Aquacultural Industry has been developed to unique industry itself, and it could be said the Hoe - korean style Sashimi or Sushi culture of korea can't exist without its aquacultural industry. So it could be said that the Aquacultural industry is not only a part of the fishery industry but also inevitable unique industry. The main objective of this paper is to analysis the present situation for production of Flatfish, distribution of Flatfish, and consumption structure of Flatfish. Especially, the production for aquacultural Flatfish in 2005 has been raised over 38 times against the production in 1990, and it takes the status as the major fish which leads the domestic aqua cultural industry compare with others. The distribution of Flatfish can be divided to the domestic and export mainly. In field of its domestic distribution, Flatfish is the major item with Rockfish, and the deal of its over 90% happens in Similarity Fishery Wholesale Markets such as In-chon, Ha-nam, and Bu-san Fishery Wholesale Market not in the common distribution process of the fishery products. At present, the exporting of Flatfish take 13.9% among the whole Aquacultural Industry of korea, and Flatfish mainly export to Japan. Also, through the development of chinese economy, Hoe consumption culture is expanded gradually. And the future of exporting Flatfish is very bright because of developing of the U.S. market. The brief introduction of the consumption style of live fish is as belows. According to the research, generally the most of korean consumers prefer individual item as their food to combination style in korean Hoe consumption culture and the favorite item of korean consumers are Flatfish and Rockfish.

• 상하수도학회지
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• 제32권5호
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• pp.421-434
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• 2018

Water supply/intake pumps operation use 70~80% of power costs in water treatment plants. In the water treatment plant, seasonal and hourly differential electricity rates are applied, so proper pump scheduling can yield power cost savings. Accordingly, the purpose of this study was to develop an optimal water supply pump scheduling scheme. An optimal operation method of water supply pumps by using genetic algorithm was developed. Also, a method to minimize power cost for water supply pump operation based on pump performance derived from the thermodynamic pump efficiency measurement method was proposed. Water level constraints to provide sufficient disinfection performance in a clearwell and reservoirs were calibrated. In addition, continuous operation time constraints were calibrated to prevent frequent pump switching. As a result of optimization, savings ratios during 7 days in winter and summer were 4.5% and 5.1%, respectively. In this study, the method for optimal water pump operation was developed to secure disinfection performance in the clearwell and to save power cost. It is expected that it will be used as a more advanced optimal water pump operation method through further studies such as water demand forecasting and efficiency according to pump combination.

• 응용통계연구
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• 제32권6호
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• pp.851-865
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• 2019

하나의 시계열 자료에서 다양한 특징을 발견하는 일은 간단한 문제가 아니다. 본 논문에서는 하나의 시계열 자료에서 복수의 패턴을 찾아내어 예측 정확도를 높이는 방식인 다중 결합 예측 알고리즘을 소개한다. 이 알고리즘은 시간적 결합과 예측값 조합의 개념을 사용한다. 시간적 결합 방식을 통해, 하나의 시계열 자료에서 여러 개의 시계열 자료를 생성할 수 있으며, 각각의 자료는 별도의 특성을 가지게 된다. 여러 개의 시계열 자료에서 다양한 특성을 추출하기 위하여 지수평활법을 사용하고 시계열 요소들 및 이들의 예측값을 계산한다. 마지막 단계에서 시계열 요소 별로 예측값을 혼합 한 후, 각 시계열 요소들의 조합값을 더하여 최종 예측값을 만든다. 실증 분석으로 국내 교통사고 발생 건수를 예측한다. 분석 결과, 기존의 다른 예측 방식보다 예측 성능이 우수함을 확인할 수 있다.

• 디지털융복합연구
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• 제12권3호
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• pp.211-218
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• 2014

최근 풍력에너지는 풍력터빈의 지능화뿐만 아니라 풍력 발전량 예측 부분에서 컴퓨팅과의 결합이 확대되고 있다. 풍력 발전은 기상상태에 따라 출력변동이 심하고 출력 예측이 어려워 효율적인 전력 생산을 위해서 신재생에너지를 전력계통에 안정적으로 연계할 수 있는 기술이 필요하다. 본 논문에서는 분산형 전원의 예측정보를 향상시켜 예측한 발전량과 실제 발전량의 차이를 최소화하기 위한 분산형 전원전력의 단기예측 모델을 설계한다. 제안된 모델은 단기 예측을 위해서 물리모델과 통계모델을 결합하였으며, 물리모델에서 생산된 격자별 예측값 중 예측 지점내 예측지점의 값을 추출하고, 물리 모델 예측값에 통계모델을 적용하여 발전량 산정을 위한 최종 기상 예측값을 생성한다. 또한, 제안 모델에서는 실시간 기상청 관측자료와 실시간 중기 예측 자료를 입력 자료로 사용하여 단기 예측모델을 수행한다.

• 한국수자원학회논문집
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• 제35권4호
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• pp.411-423
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• 2002

유출에 대한 신속하고 정확한 예측은 수문 및 수자원 분야에 있어서 궁극적인 목표 중의 하나이며, 우리나라와 같이 강우에 대한 유출의 응답이 짧은 시간에 발생하는 경우에 무엇보다도 중요하다. 따라서, 토지이용변화 등에 의한 유출의 변화 및 감시를 포함하는 유역내의 수문 변수의 변화를 적절하게 고려할 수 있는 분포형 자료를 선호하게 된다. 이때 분포형 모형을 적용시키기 위해서는 강우의 공간특성을 알아야 하며, 각 격자별 강우량이 입력자료로 활용되어 각 격자별 유출특성을 파악하게 된다. Landsat TM 자료를 이용할 경우 분포형 모형을 위한 유역 내에 관련된 인자 및 식생, 토지피복 등의 자세한 정보를 제공할 수 있다. 본 연구에서는 SCS의 유출곡선번호(CN)에 의한 방법을 이용하여 유효우량도를 작성하여 신속하게 유출의 감시가 가능하도록 하는 기법에 대하여 검토하였다. 호우시에 있어서 유효우량에 대한 시계열 자료는 본 기법을 통하여 분포형태로서 계산i과 수 있으며, 이 결과는 분포형 유출모형을 이용하여 유역 출구에서의 수문곡선을 산정할 수 있다.

• 한국농공학회논문집
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• 제62권6호
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• pp.1-9
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• 2020

Reservoir storage and water level information is essential for accurate drought monitoring and prediction. In particular, the agricultural drought has increased the risk of agricultural water shortages due to regional bias in reservoirs and water supply facilities, which are major water supply facilities for agricultural water. Therefore, it is important to evaluate the available water capacity of the reservoir, and it is necessary to determine the water surface area and water capacity. Remote sensing provides images of temporal water storage and level variations, and a combination of both measurement techniques can indicate a change in water volume. In areas of ungauged water volume, satellite remote sensing image acts as a powerful tool to measure changes in surface water level. The purpose of this study is to estimate of reservoir storage and level variations using satellite remote sensing image combined with hydrological statistical data and the Normalized Difference Water Index (NDWI). Water surface areas were estimated using the Sentinel-2 satellite images in Seosan, Chungcheongnam-do from 2016 to 2018. The remote sensing-based reservoir storage estimation algorithm from this study is general and transferable to applications for lakes and reservoirs. The data set can be used for improving the representation of water resources management for incorporating lakes into weather forecasting models and climate models, and hydrologic processes.

• Wind and Structures
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• 제28권2호
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• pp.129-140
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• 2019

Accurately simulating the wind field of large-scale region, for instant urban areas, the locations of large span bridges, wind farms and so on, is very difficult, due to the complicated terrains or land surfaces. Currently, the regional wind field can be simulated through the combination of observation data and numerical model using observation-nudging in the Weather Research and Forecasting model (WRF). However, the main drawback of original observation-nudging method in WRF is the effects of observation on the surrounding field is fully mathematical express in terms of temporal and spatial, and it ignores the effects of terrain, wind direction and atmospheric circulation, while these are physically unreasonable for the turbulence. For these reasons, a spatial correlation-based observation-nudging method, which can take account the influence of complicated terrain, is proposed in the paper. The validation and comparation results show that proposed method can obtain more reasonable and accurate result than original observation-nudging method. Finally, the discussion of wind field along bridge span obtained from the simulation with spatial correlation-based observation-nudging method was carried out.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권10호
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• pp.3571-3587
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• 2021

For accurately analysing and forecasting the social networks of China's political, economic and social power elites, it is necessary to develop a database that collates their information. The development of such a database involves three stages: data definition, data collection and data quality maintenance. The present study recommends distinctive solutions in overcoming the challenges that occur in existing comparable databases. We used organizational and event factors to identify the Chinese power elites to be included in the database, and used their memberships, social relations and interactions in combination with flows data collection methodologies to determine the associations between them. The system can be used to determine the optimal relationship path (i.e., the shortest path) to reach a target elite and to identify of the most important power elite in a social network (e.g., degree, closeness and eigenvector centrality) or a community (e.g., a clique or a cluster). We have used three social network analysis tools (i.e., R, UCINET and NetMiner) in order to find the important nodes in the network. We compared the results of centrality rankings of each tool. We found that all three tools are providing slightly different results of centrality. This is because different tools use different algorithms and even within the same tool there are various libraries which provide the same functionality (i.e., ggraph, igraph and sna in R that provide the different function to calculate centrality). As there are chances that the results may not be the same (i.e. centrality rankings indicating the most important nodes can be varied), we recommend a comparison test using different tools to get accurate results.