• Journal of Korea Water Resources Association
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• v.45 no.5
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• pp.505-516
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• 2012

The study applies a hydrologic simulation model, HEC-1 developed by Hydrologic Engineering Center to Daecheong dam watershed for modeling hourly inflows of Daecheong dam. Although the HEC-1 model provides an automatic optimization technique for some of the parameters, the built-in optimization model is not sufficient in estimating reliable parameters. In particular, the optimization model often fails to estimate the parameters when a large number of parameters exist. In this regard, a main objective of this study is to develop Bayesian Markov Chain Monte Carlo simulation based HEC-1 model (BHEC-1). The Clark IUH method for transformation of precipitation excess to runoff and the soil conservation service runoff curve method for abstractions were used in Bayesian Monte Carlo simulation. Simulations of runoff at the Daecheong station in the HEC-1 model under Bayesian optimization scheme allow the posterior probability distributions of the hydrograph thus providing uncertainties in rainfall-runoff process. The proposed model showed a powerful performance in terms of estimating model parameters and deriving full uncertainties so that the model can be applied to various hydrologic problems such as frequency curve derivation, dam risk analysis and climate change study.

• Journal of Korean Society of Transportation
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• v.19 no.3
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• pp.75-88
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• 2001

Signal optimization model for alternative use of lanes at a signalized intersection with an stop-line added backward was presented in this paper. The simulation results shot-ed that the traffic fed from the stop-line passed the intersection in each specified phasing interval for left and through traffic. The experimental results indicated that the proposed model was much superior to traditional signal optimization methodology in reducing delay, fuel consumption, and disutility index for delay and stops. The effects for reducing delay were greater than those for doing fuel consumption and disutility index due to the added stop-line. The proposed model is expected to alleviate traffic congestion at intersections, both which have no left turn pocket, and which have large left turn volume. The model is recommended to adapted for intersections spaced long among them with no near driveway.

• Journal of Navigation and Port Research
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• v.36 no.1
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• pp.51-58
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• 2012

In spite of today's rapid growth of world cruise industry, little academic attention has yet been given to the decision making problems for cruise operations. This research deals with strategic cruise itinerary planning that any cruise company should face. Increasing demands for international itineraries and redeployments of cruise ships are adding complexity to the itinerary planning. A slight modification of the conventional PERT/CPM network is adopted. to cope with this complexity systematically. By this, the concept of candidate itinerary network is suggested for each cruise ship. To integrate these candidate itinerary networks for each ship in a single framework, an integer programming model has been developed to find the optimal itinerary planning for any fleet of cruise ships. A numerical example, based on real cruise itinerary practices, is tested to validate and interpret the model.

• Journal of Korea Water Resources Association
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• v.52 no.10
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• pp.707-718
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• 2019

The optimal water allocation pursues a reliable and economic supply of water resources to meet various interests in socio-economic-environmental aspects. The global water shortage has intensified due to climate change and population growth with limited water resources. Thus, the water management scheme has shifted to improve water use efficiency by proper demand management and water allocation planning. Here, a hydro-economic water allocation model, called WAMM (Water Allocation and Management Model) is introduced. The WAMM is equipped with an improved linear programming algorithm for optimal water allocation and estimates economic value of water supply as an objective of water

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.200-209
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• 2019

When forecasting future values, a model estimated after minimizing training errors can yield test errors higher than the training errors. This result is the over-fitting problem caused by an increase in model complexity when the model is focused only on a given dataset. Some regularization and resampling methods have been introduced to reduce test errors by alleviating this problem but have been designed for use with only a given dataset. In this paper, we propose a new optimization approach to reduce test errors by transforming a test error minimization problem into a training error minimization problem. To carry out this transformation, we needed additional data for the given dataset, termed pseudo data. To make proper use of pseudo data, we used three types of missing data imputation techniques. As an optimization tool, we chose the least squares method and combined it with an extra pseudo data instance. Furthermore, we present the numerical results supporting our proposed approach, which resulted in less test errors than the ordinary least squares method.

• 한국도로학회지:도로
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• v.4 no.3 s.13
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• pp.4-15
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• 2002

• Journal of the Korean Society for Railway
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• v.13 no.5
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• pp.535-540
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• 2010

We present an optimization model for how to assign the freight trains to transshipment tracks and allocate the containers to the freight trains in a rail container terminal. We formulate this problem as a multi-criteria integer programming to minimize the makespan of job schedule and simultaneously to maximize the loading throughput, i.e. the number of containers to be disposed per day. We also apply our model to the instance obtained from the real-world data of the Uiwang Inner Container Depot. From the experiments, we can see an improvement of approximately 6% in makespan, which means that our model can contribute to the improvement of the disposal capacity of containers without additional expansion of facilities.

• Journal of Korea Water Resources Association
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• v.39 no.11 s.172
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• pp.977-984
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• 2006

The parameters in the Horton's model which has well known as typical infiltration model were determined by the use of the optimization technique. It was assumed the initial infiltration capacity in this model was related to the antecedent precipitation per 10 days with linear combination. And both the parameters of the ultimate infiltration capacity and the decay factor were determined uniquely on a basin. Thus the optimal model's parameters representative to a basin were obtained and the Horton's infiltration equations by rainstorm events were determined. The data of ten rainstorm events for this study were observed at the Jeonjeokbigyo station located at the Selmacheon experimental basin that was $8.5km^2$ wide in the Imjin river.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.415-415
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• 2023

홍수는 일반적으로 많은 피해와 인명 손실을 초래하는 자연재해 중 하나로, 홍수위 예측은 이를 방지하고 대처하는 데 중요한 역할을 한다. 최근 기계학습 기술을 이용하여 홍수위 예측 모델을 개발하고자 하는 연구가 많이 진행되고 있다. 특히, LSTM(long short-term memory) 모형은 시계열 예측에 대해 검증된 모형으로 홍수위 예측 연구에도 활발하게 적용되고 있다. 하지만 기계학습 모델의 학습 성능은 하이퍼파라미터의 값에 영향을 크게 받을 수 있으며, 특히 집중호우로 인해 수위가 급변하는 경우에는 과거 시계열 자료에 영향을 받는 LSTM 모형의 예측 성능이 오히려 낮게 나타날 수 있다. 따라서 본 연구에서는 홍수위 예측시 LSTM 모형의 예측 성능을 향상시킬 수 있는 세부 하이퍼파라미터 값을 분석하여 최적의 하이퍼파라미터 조합을 제안하고자 한다. 이를 위해 하이퍼파라미터 조정을 위한 자동화 도구인 W&B(Weights&Bias)의 Sweep 기능을 적용하고자 한다. 본 연구를 통해 LSTM 모형을 적용한 홍수위 예측의 정확도를 향상시키는 데에 기여할 수 있을 것으로 기대된다.

• Journal of Korea Water Resources Association
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• v.52 no.8
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• pp.565-573
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• 2019

An optimization model of water intake planning is developed based on a linear programming (LP) for the intelligent water purification plant operation system. The proposed optimization model minimizes the water treatment costs of raw water purification by considering a time-delay of treatment process and hourly electricity tariff, which is subject to various operation constraints, such as water intake limit, storage tank capacity, and water demand forecasts. For demonstration, the developed model is applied to H water purification center. Here, we have tested three optimization strategies and the results are compared and analyzed in economic and safety aspects. The optimization model is expected to be used as a decision support tool for optimal water intake scheduling of domestic water purification centers.