• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.307-307
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• 2022

최근 기후변화와 댐 상류 토지이용 변화 등과 같은 다양한 원인에 의해 댐 유입량의 변동성이 증가하면서 댐 관리 및 운영조작 의사 결정에 어려움이 발생하고 있다. 따라서 이러한 댐 유입량의 변동 특성을 반영하여 댐 유입량을 정확하고 효율적으로 예측할 수 있는 방안이 필요한 실정이다. 머신러닝 기술이 발전하면서 Auto-ML(Automated Machine Learning)이 다양한 분야에서 활용되고 있다. Auto-ML은 데이터 전처리, 최적 알고리즘 선택, 하이퍼파라미터 튜닝, 모델 학습 및 평가 등의 모든 과정을 자동화하는 기술이다. 그러나 아직까지 수문 분야에서 댐 유입량을 예측하기 위한 모델을 개발하는데 있어서 Auto-ML을 활용한 사례는 부족하고, 특히 댐 유입량의 예측 정확성을 확보하기 위해 High-inflow and low-inflow 의 변동 특성을 고려한 하이브리드 결합 방식을 통해 Auto-ML 기반 앙상블 모델을 개발하고 평가한 연구는 없다. 본 연구에서는 Auto-ML의 패키지 중 Auto-sklearn을 통해 홍수기, 비홍수기 유입량 변동 특성을 반영한 하이브리드 앙상블 댐 유입량 예측 모델을 개발하였다. 소양강댐을 대상으로 적용한 결과, 하이브리드 Auto-sklearn 앙상블 모델의 댐 유입량 예측 성능은 R² 0.868, RMSE 66.23 m³/s, MAE 16.45 m³/s로 단일 Auto-sklearn을 통해 구축 된 앙상블 모델보다 전반적으로 우수한 것으로 나타났다. 특히 FDC (Flow Duration Curve)의 저수기, 갈수기 구간에서 두 모델의 유입량 예측 경향은 큰 차이를 보였으며, 하이브리드 Auto-sklearn 모델의 예측 값이 관측 값과 더욱 유사한 것으로 나타났다. 이는 홍수기, 비홍수기 구간에 대한 앙상블 모델이 독립적으로 구축되는 과정에서 각 모델에 대한 하이퍼파라미터가 최적화되었기 때문이라 판단된다. 향후 본 연구의 방법론은 보다 정확한 댐 유입량 예측 자료를 생성하기 위한 방안 수립뿐만 아니라 다양한 분야의 불균형한 데이터셋을 이용한 앙상블 모델을 구축하는데도 유용하게 활용될 수 있을 것으로 사료된다.

• Journal of the Korean Home Economics Association
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• v.40 no.8
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• pp.153-166
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• 2002

This study aims to reveal the influence of price increase in gasoline on household expenditure trade-off. The subjects were 651 households, acquired the first quarter of 1996 and 1997. This study shows the change of the auto fuel budget share in the same household and they were analyzed with the paired t-test, independent t-test. The results are as follows; 1) the price increase of auto gasoline resulted in the increase of its budget share, regardless of a household's true increase or decrease of income. 2) according to price increase in gasoline, the auto fuel budget share has been changed, therefore I divided these changes into three group on the base of it's degree of change. 3) In the group that had a decrease in auto fuel budget share compared to the degree of change, there was a trade-off between the increase in food and light & light water and the decrease of education and auto fuel budget share. Auto fuel in this group was used as discretionary good. 4) In the group that had a similar change in auto fuel budget share compared to the degree of change, there were no trade-off between expenditure items except auto fuel budget share and miscellaneous decrease. This group is the highest income group among the three groups. 5) In the group that had and increase of change in auto fuel budget share compared to the degree of change, there was a trade-off between the increase of eating-out and auto fuel, and the decrease of education and miscellaneous budget share. Auto fuel in this group was used as a discretionary good. 6) trade-off expenditure budget share showed a mixed effect between the influence of increase in gasoline price and influence of increase in true income.

• The monthly packaging world
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• s.113
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• pp.126-131
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• 2002

• International Commerce and Information Review
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• v.8 no.3
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• pp.299-321
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• 2006

The purpose of this study was to analyze export competitiveness of Korean auto parts and Chinese auto parts in U.S. market by using Index of Export Bias and Market Comparative Advantage Index. For attaining the purpose of study, we classified the auto parts which exported to U.S. market and the imported products by using the six units classification of the Harmonized System(HS). Analyzing period was 1998-2005. The analysis of Korean results of MCA indicated that the Korean auto parts which gained export competitiveness in the U.S. market were HS Code No. 8708.94, 8708.99, 8708.92. The products which will have export competitiveness in the U.S. market would be HS Code No. 8708.93, 8708.39, 8708.60 respectively. On the other hand, the results indicated that the Chinese auto parts which gained export competitiveness in the U.S. market were HS Code No. 8708.70, 8708.31, 8708.91, 8708.60, 8708.39. From this study, we find the following strategies for successful advancing into the U.S. and world market. i) Linking strategy through working cooperation with local auto firms, government and academic world. ii) Advance strategy of auto firm accompany by module working and system auto parts firm. iii) Retention strategy of large technical institution established by auto parts firms and taking cooperation of auto firms iv) Settlement strategy for having weaken competitive article and production field. v) Cost-cutting strategy through strengthening logistics cooperation system between auto parts firms and auto firms. vi) Active invitation strategy of foreign investment under quickly cooperating of government.

• Korea Trade Review
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• v.44 no.3
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• pp.253-269
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• 2019

This study examines the utilization effect of FTA on the sales and profit of the secondary auto-part suppliers in two aspects: 1) firm-level survey on the utilization of FTA and 2) statistical inference on the FTA effects on their sales and profit. We use the GLS statistical technique, panel and survey data of 130 secondary auto-part suppliers in the Daegu and Kyungpook area in 2007-2016. The evidence shows that the secondary auto-part suppliers struggle to prepare documents for the FTA certificates of origin due to their small firm size, although they utilize the FTA at the relatively high rate of 92 percent. Statistical evidence shows that an increase in the export of the first vender significantly affects the sale of the secondary auto-part vendors, but not their profit. The low profit and high managing cost of utilizing the FTA deteriorate the utilization effect of the FTA of the secondary auto-part vendors, which is a key factor in a global supply chain and for the competitiveness of the automobile industry. Government policies are required for the secondary auto-part suppliers to utilize the FTA more effectively and share the benefits of tariff reduction with first auto-part vendors under FTA transaction.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.4
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• pp.483-488
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• 2010

An online monitoring based upon sensor system is essential to assure both efficient operation and safety in the power plant. Of great importance is modeling for auto-association (AA) in online monitoring technique. The objective of auto-associative models lies in predicting true values of plant operation parameters from sensor signals transmitted. This paper presents two AA models using Support Vector Regression (SVR) and Partial Least Square Regression (PLSR). The presented models are useful, in particular, when there are many parameters to monitor in the power plant. Illustrative examples are given by using a real-world plant dataset. AA performances of SVR and PLSR are finally summarized in terms of accuracy and sensitivity. According to our results, SVR shows much higher accuracy and, however, its sensitivity is relatively degraded.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.19-19
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• 2011

The appraisals of hydrology model behavior for flow and water quality are generally performed through comparison of simulated data with observed ones. To perform appraisal of hydrology model, some criteria are often used, such as coefficient of determination ($R^2$), Nash and Sutcliffe model efficiency coefficient (NSE), index of agreement (d), modified forms of NSE and d, and relative efficiency criteria NSE and d. These criteria are used not only for hydrology model estimations also for various comparisons of two data sets; This NSE has been often used for SWAT calibration. However, it has been known that the NSE value has some limitations in evaluating hydrology at watersheds under monsoon climate because this statistic is largely affected by higher values in the data set. To overcome these limitations, the SWAT auto-calibration module was enhanced with K-means clustering and direct runoff/baseflow modules. However the NSE is still being used in this module to evaluate model performance. Therefore, the SWAT Auto-calibration module was modified to incorporate alternative efficiency criteria into the SWAT K-means/direct runoff-baseflow auto-calibration module. It is expected that this enhanced SWAT auto-calibration module will provide better calibration capability of SWAT model for all flow regime.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.539-539
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• 2012

최근 미국 환경부에서는 국가 환경 정책으로써 LID(Low Impact Development)를 대안 책으로 제시하고 있으며 우리나라에서도 최근 LID기법 연구가 활발히 진행 되고 있다. LID란 기존의 집중식 BMP처럼 유출 발생 후 처리를 다루는 방식의 기법이 아닌 발생원 단계에서의 처리에 초점을 맞춘 기법이다. 환경적 측면에서 다양한 기능을 가능하게 할 수 있는 LID기법 적용에 따른 효과를 알아보기 위해 전 세계적으로 SWMM 모형이 많이 사용되고 있지만 SWMM 모형 내 유량 및 수질에 따른 자동 보정 툴이 존재하지 않고 유역에 적합한 최적의 LID 기법 구조물의 설계 기준을 정할 수 있는 툴이 존재하지 않기 때문에 보다 효율적인 유역의 수문 보정 및 LID 기법 적용에 따른 효과 모의를 제공하지 못한다. 따라서 본 연구에서는 SWMM 5.0 버전 내 SWMM LID auto-calibration tool을 PARASOL 알고리즘을 기반으로 개발하였다. 또한 개발된 PARASOL 알고리즘 기반 SWMM LID auto-calibration tool을 이용하여 경기도 경안천 유역에 적용하였고 2011년 일별 실측 수문자료와 비교 분석 하였으며 경기도 경안천 유역에 맞는 최적의 LID기법을 산정하였다. 본 연구에서 개발 된 SWMM auto-calibration tool은 SWMM 모형의 유량 및 수질을 자동으로 보정하기 때문에 보다 효율적인 모형의 보정을 사용자에게 제공해 줄 수 있을 것이며 유역에 적합한 최적의 LID 기법 구조물 설계를 제시해 줄 수 있기 때문에 향후 LID 기법을 이용한 도시개발 계획에 유용하게 사용될 수 있을 것으로 판단된다. 향후 PARASOL 알고리즘 뿐만이 아닌 GLUE, SUFI-2, GA 등 다양한 알고리즘이 추가된 SWMM LID auto-calibration tool 을 개발 중에 있다.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.53-59
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• 2021

According to the Korean Traffic Accident Analysis System (TAAS), more than 200,000 traffic accidents occur every year. Also, the statistics including auto insurance companies data show 1.3 million traffic accidents. In the case of TAAS, the types of traffic accidents are simply divided into four; frontal collision, side collision, rear collision, and rollover. However, more detailed information is needed to assess for advanced driver assist systems at intersections. For example, directional information is needed, such as whether the vehicle in the car accident way in a straight or a left turn, etc. This study intends to redefine the type of accident with the more clear driving direction and path by referring to the Negligence standards used in automobile insurance accidents. The standards largely divide five categories of car-to-car/motorcycle /pedestrian/cyclist, and highway, and the each category is classified into dozens of types by status of the traffic signal, conflict situations. In order to present more various accident types for auto insurance accidents, the standards are reclassified driving direction and path of vehicles from crash situations. In results, the car-to-car accidents are classified into 33 accident types, car-to-pedestrian accidents have 19 accident types, car-to-motorcycle accidents have 38 accident types, and car-to-cyclist accidents are derived into 26 types.

• International Commerce and Information Review
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• v.7 no.4
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• pp.351-365
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• 2005

Korean auto mobile industry has been contributed to development on national economy for last 30 years. Especially, The fact is that latest increasement of Korean automobile selling is worthy of notice in U.S. market which is the biggest automobile market of the world. But development of automobile industry unattainable nothing of helping of auto parts industry. So, when we discuss about growth of automobile industry, we also have to consider role of auto parts industry at the same time. The purpose of this study was to analyze exporting competition of Korean auto parts in U.S. market by using Index of Export Bias and Market Comparative Advantage Index. For attaining the purpose of study, we classified the Korean auto parts which exported to U.S. market and the world by using the six units classification of the Harmonized System(HS). Also we measured Index of Export Bias and Market Comparative Advantage Index. Analyzing period was 1998-2004. The results of Index of Export Bias indicated that HS Code No. 8708.50, 8708.91 represented over 3 numerical value and 8708.92, 8708.60, 8708.39, 8708.29 represented over 2 numerical value. Additional results indicated that the Korean auto parts which gained exporting competition in the U.S. market were HS Code No. 8708.70, 8708.93, 8708.92. The products which will have exporting competition in the U.S. market would be HS Code No. 8708.99,