• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.71-79
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• 2005

Existing arterial link travel time estimation methods relying on either aggregate point-based or individual section-based traffic data have their inherent limitations. This paper demonstrates the utility of data fusion for improving arterial link travel time estimation. If the data describe traffic conditions, an operator wants to know whether the situations are going better or worse. In addition, some traffic information providing strategies require predictions of what would be the values of traffic variables during the next time period. In such situations, it is necessary to use a prediction algorithm in order to extract the average trends in traffic data or make short-term predictions of the control variables. In this research. a multi-step ahead prediction algorithm using Data fusion was developed to predict a link travel time. The algorithm performance were tested in terms of performance measures such as MAE (Mean Absolute Error), MARE(mean absolute relative error), RMSE (Root Mean Square Error), EC(equality coefficient). The performance of the proposed algorithm was superior to the current one-step ahead prediction algorithm.

• International Journal of Highway Engineering
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• v.10 no.4
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• pp.151-159
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• 2008

Performances of retroreflectivity vary place to place, according to traffic volumes and time lengths after striping, depending on pavement marking materials and colors. The present paper uses the nation wide data of retroreflectivity, which has been collected from freeways and then tries to develop the regression curve setting traffic volume and service life as independent variables and retroreflectivities as dependent variables. The DB system includes two year's measurement in $2005{\sim}2006$ over Korean freeway pavement marking at an interval of three months for the period. The mobile measurement system, a laserlux, was employed for the purpose. The DB has provided a lot of information about materials and performance of the specific pavement marking such as geometric features, traffic volumes, material characteristics and the installation date. This study provides the comparison of pavement marking performances under diversified conditions. Based on accumulated pavement marking performances, this study provides performance curves based on the diversified factors. The goal of the retroreflectivity modeling is to develop equations that can be used to estimate an average retroreflectivity of pavement markings as a function time since application and traffic volume. After representing the variation of retroreflectivities and estimating regression curves by linear, exponential, logarithmic and power function, the regression curve which had the highest coefficient of determination and the value similar to the last field measurement was regarded as the retroreflectivity decay model. As a result of verification, the decay model showed the signification within the 90% confidence level and especially showed the clear relation with field data according to increase of cumulative vehicle exposure. Accordingly, these models can be used to determine service lives, retroreflectivity degradation rates, and retroreflectivity of new markings.

• Journal of the Economic Geographical Society of Korea
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• v.22 no.3
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• pp.351-365
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• 2019

This study aims to predict the changes in population distribution in Korea by considering spatio-temporal characteristics of major migration reasons. For the purpose, we analyze the spatio-temporal characteristics of each major migration reason(such as job, family, housing, and education) and estimate the transition probability, respectively. By appling Markov chain model processes with the ChapmanKolmogorov equation based on the transition probability, we predict the changes in the population distribution for the next six years. As the results, we found that there were differences of population changes by regions, while there were geographic movements into metropolitan areas and cities in general. The methodologies and the results presented in this study can be utilized for the provision of customized planning policies. In the long run, it can be used as a basis for planning and enforcing regionally tailored policies that strengthen inflow factors and improve outflow factors based on the trends of population inflow and outflow by region by movement factors as well as identify the patterns of population inflow and outflow in each region and predict future population volatility.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.39-39
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• 2018

우리나라는 전체 국토의 약 70%가 산악지형으로 이루어져 있고 연중 강우가 6월에서 9월에 집중되는 기후적 특성을 가지고 있다. 최근 기후변화의 영향까지 더해지면서 시간당 300mm 이상의 집중호우를 보이는 이상강우가 빈번하게 발생하고 있다. 대부분의 도시지역은 하천을 중심으로 발달되어 있어 인구 및 사회기반시설의 집약정도가 매우 높고 하천변 저지대 지역에 주거 및 상업시설이 밀집되어 있다. 기후적 지역적 특성으로 인한 홍수피해를 미연에 방지하고 피해를 최소화하기 위하여 치수 중심의 수자원 관리를 위해 노력하고 있다. 하지만 우리나라의 하천관리는 시기별 하천 수량의 급격한 변동으로 어려움을 겪고 있다. 이러한 어려움을 극복하고 효율적인 수자원 관리 및 홍수피해 저감을 위해 수계를 중심으로 20개의 다목적댐을 건설하여 운영 관리 중에 있다. 특히, 홍수기 시 댐 운영은 예상 강우에 따라 적절한 예비방류와 강우 시 효율적인 댐 운영계획이 필수적이다. 본 연구에서는 강우가 집중되는 홍수기 댐 운영 시에 예상 강우량에 따라 댐 유역 내 유량 증가에 기여하는 정도를 예측할 수 있는 유출율 예측 회귀식을 개발하였다. 유출율은 강우와 유출량의 비로 지역특성, 강우특성, 관개여부, 선행강우량, 강우이동 방향 등 다양한 요인에 의해 복잡한 메케니즘을 갖는다. 단순히 예상되는 총강우량에 따른 유출율 만으로 상호관계를 정의하기가 쉽지 않기 때문에 한국수자원공사에서 개발한 댐군 홍수조절 연계운영시스템(COSFIM)인 수문학적 연계운영모형을 활용하였다. 최근 10년간 홍수기에 발생한 강우사상별 시간단위의 수문자료(총강우량, 기저유량, 유출율, 무강우일수, 강우지속시간 등) 분석을 실시하였다. COSFIM 모형을 통한 결과를 토대로 고려항목 간 교차검증을 통해 사분위수범위의 이상치 경계를 설정하고 상관분석 결과에 따라 0.5 이상의 상관성이 높은 항목을 활용하여 예측 강우량에 따른 유출율 예측 회귀식을 도출하였다. 본 연구에서 개발한 예측 강우에 따른 유출율 예측 산정식은 댐 유역에 예상되는 강우량에 대하여 하천의 유량 증가 예측 정도를 정량적으로 제시할 수 있으며, 실제 홍수기 댐 운영 시 예상 강우량에 따라 신속하고 적절한 수문 방류 계획 수립에서 용이하게 활용할 수 있을 것으로 기대한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.412-424
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• 2019

In this study, the changes of the streamflow characteristics of the watershed were analysed depending on the infiltration methods of CAT. The study area, Boryeong-dam watershed located in Chungcheongnam-do area, has been suffered from severe drought in recent years and stabilized regarding on the storage rate through efforts such as constructing a channel connecting the upstream of Boryeong-dam from the downstream of the Geum river. In this study, the effects of soil infiltration parameters on the watershed streamflow characteristics were analyzed by the infiltration methods of CAT such as Rainfall Excess, Green&Ampt and Horton. And the parameter calibrations were conducted by SCEUA-P, a global optimization technique module of the PEST, the package for parameter optimization and uncertainty analysis, to compare the yearly variations of soil parameters for infiltration methods of CAT. In addition, the streamflow characteristics were analyzed for three infiltration methods by applying three different scenarios, such as applying calibrated parameters for every years to simulate the model for each years, applying calibrated parameters for the entire period to simulate the model for entire period, and applying the average value of yearly calibrated parameters to simulate the model for entire period.

• Journal of Korea Water Resources Association
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• v.54 no.3
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• pp.181-190
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• 2021

In this study, a large-scale levee breach experiment from lateral overflow was conducted to verify the effect of the new reinforcement method applied to the levee's surface. The new method could prevent levee failure and minimize damage caused by overflow in rivers. The levee was designed at the height of 2.5 m, a length of 12 m, and a slope of 1:2. A new material mixed with biopolymer powder, water, weathered granite, and loess in an appropriate ratio was sprayed on the levee body's surface at a thickness of about 5 cm, and vegetation recruitment was also monitored. At the Andong River Experiment Center, a flow (4 ㎥/s) was introduced from the upstream of the A3 channel to induce the lateral overflow. The change of lateral overflow was measured using an acoustic doppler current profiler in the upstream and downstream. Additionally, cameras and drones were used to analyze the process of the levee breach. Also, a new method using 3D point cloud for calculating the surface loss rate of the levee over time was suggested to evaluate the performance of the levee reinforcement method. It was compared to existing method based on image analysis and the result was reasonable. The proposed 3D point cloud methodology could be a solution for evaluating the performance of levee reinforcement methods.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.1-14
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• 2021

Onions are a representative produce that requires supply-demand control measures due to large fluctuations in production and price by growing season. Accurate forecasts of crop production can improve the effectiveness of such measures. However, it is challenging to obtain accurate estimates of crop productivity for onions because they are mainly grown on the open fields. The objective of this study was to perform the empirical analysis of the relationship between factors for crop growth and meteorological conditions, which can support the development of models to predict crop growth and production. The growth survey data were collected from open fields. The survey data included the weight of above ground organs as well as that of the bulbs. The estimates of meteorological data were also compiled for the given fields. Correlation analysis between these factors was performed. The random forest was also used to compare the importance of the meteorological factors by the growth stage. Our results indicated that insolation in early March had a positive effect on the growth of the above-ground. There was a negative correlation between precipitation and the growth of the above-ground at the end of March although it has been suggested that drought can deter the growth of onion. The negative effects of precipitation and daylight hours on the growth of the above-ground and under-ground were significant during the harvest period. These meteorological factors identified by growth stage can be used to develop models for onion growth and production forecast.

• Korea Trade Review
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• v.43 no.5
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• pp.47-66
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• 2018

This study analyzes the potential economic effects of a trade war between the U.S. and China. The CGE model is used to estimate the macroeconomic variables of each country and the change in imports/exports by industry by considering three different scenarios: (i) the US imposes a 25% of tariff on China; (ii) the US and China impose a 25% tariff bilaterally; (iii) the United States expands protection in vehicles and metals to Korea, Japan, and the EU. According to the results of the study, when the US and China initiate a trade war, GDP and welfare of both countries decline. China's decline in GDP and welfare are larger than those of the United States, which implies a trade war is more favorable to the U.S. than to China. In the long run, China's GDP and welfare decline widens further. While the trade volumes of the US and China are greatly reduced, the trade volumes of other countries does not significantly fluctuate. Finally, if the US extends protection policy to Korea, Japan and the EU, it creates undesirable effects on the US. In particular, damage to the US jeopardizes its advantageous position in a trade war with China. In order to emphasize the unfairness of protectionist policy and the damage to Korean industry, Korea needs to establish a strategy to counter US protectionist policy.

• Journal of Navigation and Port Research
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• v.48 no.3
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• pp.192-199
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• 2024

Wave overtopping is a significant natural hazard that occurs in coastal areas, primarily driven by high waves, particularly those generated during typhoons, which can cause coastal flooding. The development of residential and commercial areas along the coast, driven by increasing social and economic demands, has led to a concentration of people and assets in these vulnerable areas. This, coupled with long-term sea level rise and an increase in typhoon frequency, has heightened the risk of coastal hazards. Traditionally, the evaluation of wave overtopping volumes has relied on directly measuring the collected volume of water that exceeds the crest height of structures through hydraulic model experiments. These experiments are averaged over a specific measurement period. However, in this study, we propose a new method for estimating individual wave overtopping volumes. We utilize the temporal variation of wave overtopping heights to develop an observation system that can quantitatively assess wave overtopping volumes in actual coastal areas. To test our method, we conducted hydraulic model experiments on rubble mound breakwaters, which are commonly installed along the Korean coast. We introduce wave overtopping discharge coefficients, assuming that the inundation velocity from the structure's crest is the long-wave velocity. We then predict overtopping volumes based on wave overtopping heights and compare and review the results with experimental data. The findings of our study confirm the feasibility of estimating wave overtopping volumes by applying the overtopping discharge coefficients derived in this study to wave overtopping heights.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.363-372
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• 2016

Two-stage sample designs are commonly used for household surveys in Korea using as clusters the enumeration districts (EDs). Since clustering decomposes the population variation into within- and between-cluster variations, the sample sizes allocated in stages can affect the overall precision. Alternative clusters are often considered due to diverse reasons such as the EDs' limitation in size, being out-of-date, and in-assessibility to their household lists. In addition, the EDs are currently under development by the Statistics Korea as an joint effort toward their transition from the traditional practice to the register census from 2015. We present an approach for evaluating the difference in the precision of the mean estimators of the sets of the cluster units in between a hierachical and nested form, where the design effect is used to reflect the effect of the clustering and the sample allocation. We also demonstrate our approach using the U.S. Census counts from the year 2000 for Anne Arundel County in Maryland. Our research shows that the within-cluster variance can be significantly different for survey variables and thus the choice of cluster units and the associated sample allocation scheme should reflect the corresponding variance decomposition due to clustering.