• Journal of the Society of Naval Architects of Korea
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• v.51 no.6
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• pp.530-538
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• 2014

The weight estimation of floating offshore structures such as FPSO, TLP, semi-Submersibles, Floating Offshore Wind Turbines etc. in the preliminary design, is one of important measures of both construction cost and basic performance. Through both literature investigation and internet search, the weight data of floating offshore structures such as FPSO and TLP was collected. In this study, the weight estimation model was suggested for FPSO. The weight estimation model using non-linear regression analysis was established by fixing independent variables based on this data and the multiple regression analysis was introduced into the weight estimation model. Its reliability was within 4% of error rate.

• Korean Journal of Construction Engineering and Management
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• v.5 no.6 s.22
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• pp.138-145
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• 2004

The construction duration for any building or facilities such as high school building influence the quality of the building as well as the total cost for them. Since there are no guidelines to estimate construction duration correctly, an employer(or owner) estimate it by their own experience or intuition. Therefore some conflicts related to construction duration happen between contract parties during construction. The purpose of this study is to suggest a predictive model which helps decision makers calculate exact net working days for high school building construction at the early stage of the construction project. To measure net working days for high school construction, 15 data were collected from actual spot in Incheon region. Multiple linear regression analysis was conducted to obtain the model which calculate construction duration for the substructure, the superstructure and the finishing works. total construction duration could be obtained by adding net working days to non working days which would be based on the meteorological statistics for Incheon region since 1974 to 2003.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.109-118
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• 2011

In this research estimated accuracies that were results in all the area of filtering of the plane equation that was used by whole data set, and regional of filtering that was driven by the plane equation for each vertual Grid. All of this estimates were based by all the area of filtering that deduced the plane equation by multiple linear regression analysis that was used by ground data set. Therefore, accuracy of all the area of filtering that used whole data set has been dropped about 2~3% when average of accuracy of all the area of filtering was based on ground data set while accuracy of Regional of filtering dropped 2~4% when based on virtual Grid. Moreover, as virtual Grid which was set 3~4 cm was difference about 2% of accuracy from standard data. Thus, it leads conclusion of set 3~4 times bigger size in virtual Grid filtering over LiDAR scan gap will be more appropriated. Hence, the result of this research allow us to conclude that there was difference in average accuracy has been noticed when we applied each different approaches, I strongly suggest that it need to research more about real topography for further filtering accuracy.

• Journal of Korean Society of Transportation
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• v.31 no.1
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• pp.65-76
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• 2013

Traffic accidents at signalized intersections have been increased annually so that it is required to examine the causation to reduce the accidents. However, the current existing accident models were developed mainly by using non-linear regression models such as Poisson methods. These non-linear regression methods lack to reveal the complicated causation for traffic accidents, though they are the right choice to study randomness and non-linearity of accidents. Therefore, it is required to utilize another statistical method to make up for the lack of the non-linear regression methods. This study developed accident prediction models for 4 legged signalized intersections with Poisson methods and compared them with structural equation models. This study used structural equation methods to reveal the complicated causation of traffic accidents, because the structural equation method has merits to explain more causational factors for accidents than others.

• Tunnel and Underground Space
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• v.28 no.6
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• pp.651-669
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• 2018

This study suggests the prediction model to estimate the specific energy of a pick cutter using a gene expression programming (GEP) and particle swarm optimization (PSO). Estimating the performance of mechanical excavators is of crucial importance in early design stage of tunnelling projects, and the specific energy (SE) based approach serves as a standard performance prediction procedure that is applicable to all excavation machines. The purpose of this research, is to investigate the relationship between UCS and BTS, penetration depth, cut spacing, and SE. A total of 46 full-scale linear cutting test results using pick cutters and different values of depth of cut and cut spacing on various rock types was collected from the previous study for the analysis. The Mean Squared Error (MSE) associated with the conventional Multiple Linear Regression (MLR) method is more than two times larger than the MSE generated by GEP-PSO algorithm. The $R^2$ value associated with the GEP-PSO algorithm, is about 0.13 higher than the $R^2$ associated with MLR.

• Journal of Korea Technology Innovation Society
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• v.13 no.4
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• pp.738-757
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• 2010

Generally, it is known that the agglomeration economies appear in some industry clusters which were developed naturally. But, in Korea, most of industry clusters were built by government. This research was carried out to evaluate the performance of governments zoning investment, in other words, industry cluster policy. In this research, we use the data of manufacturing firms in Kyunggi-province. For the microeconomic analysis, we use the KIS-VALUE data of 2008. As the empirical test methods we use both multiple regressions and Propensity Score Matching. In conclusion, there is no evidences that firms in industry cluster have better performances. Surprisingly, in PSM analysis, we find the evidence that firms in industry cluster show less innovative performance.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.182-182
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• 2015

우리나라에서는 강우관측시스템의 지역적 불균형으로 상대적으로 소규모 저수지의 경우 미계측유역의 특성을 가지며, 신뢰성 있는 강우량, 유출량, 증발량 자료가 매우 부족한 실정이다. 다목적댐 유역과 같은 계측유역의 경우 상류유역의 유입량 자료의 확보가 용이하지만 대부분의 유역의 경우 계측장비가 부족하여 신뢰성이 확보된 유입량 자료를 얻는데 많은 어려움이 있다. 본 연구에서는 미계측유역의 유입량 산정을 위하여 계측유역을 대상으로 강우-유출 모형의 매개변수를 산정하였으며, 산정된 매개변수를 유역특성인자와의 상관성을 토대로 다중선형회귀분석기법(multiple linear regression, MLR)을 적용하여 지역화(regionalization)를 위한 회귀식을 도출하였다. 이를 위해 양질의 유량자료가 확보된 K-water 17개 댐 유역을 대상으로 매개변수를 산정하였으며 이 중 2개의 댐 유역을 미계측유역으로 간주하여 개발된 모형을 검증하였다. 대부분의 통계 지표에서 우수한 모의능력을 확인하였으며, 본 연구를 통하여 개발된 지역화 기법을 미계측유역에 활용한다면 보다 정량적이고 효율적인 수자원 계획이 가능할 것으로 판단된다. 향후 연구로는 불확실성을 고려한 Bayesian GLM 모형을 이용한 지역화기법을 개발하여 매개변수의 불확실성까지 고려할 수 있는 방안을 모색하고자 한다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.9
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• pp.929-936
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• 2015

Nacelle anemometers are mounted on wind-turbine nacelles behind blade roots to measure the free-stream wind speed projected onto the wind turbine for control purposes. However, nacelle anemometers measure the transformed wind speed that is due to the wake effect caused by the blades' rotation and the nacelle geometry, etc. In this paper, we derive the Nacelle Transfer Function (NTF) to calibrate the nacelle wind speed to the free-stream wind speed, as required to carry out the performance test of wind turbines according to the IEC 61400-12-2 Wind-Turbine Standard. For the reference free-stream wind data, we use the Light Detection And Ranging (LiDAR) measurement at the Shinan wind power plant located on the Bigeumdo Island shoreline. To improve the simple linear regression NTF, we derive the multiple nonlinear regression NTF. The standard error of the wind speed was found to have decreased by a factor of 9.4, whereas the mean of the power-output residual distribution decreased by 6.5 when the 2-parameter NTF was used instead of the 1-parameter NTF.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.406-411
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• 2013

Big data issue has been considered in diverse fields. Also, big data learning has been required in all areas such as engineering and social science. Statistics and machine learning algorithms are representative tools for big data learning. In this paper, we study learning tools for big data and propose an efficient methodology for big data learning via legacy data to practical application. We apply our big data learning to patent analysis, because patent is one of big data. Also, we use patent analysis result for technology forecasting. To illustrate how the proposed methodology could be applied in real domain, we will retrieve patents related to big data from patent databases in the world. Using searched patent data, we perform a case study by text mining preprocessing and multiple linear regression of statistics.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.207-207
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• 2019

최근 우리나라는 지역 특성 및 기후변화의 영향으로 인해 수문학적 요소의 변동성이 커지고 수자원의 지속적인 관리에 있어 유출량은 중요한 문제로 여겨지고 있다. 특히 일부 소하천 또는 접경지역과 같은 미계측유역은 수문학적 요소에 대한 자료가 부족하고 수문모형의 초기치 설정과 과거 유출량 자료를 통하여 최적화한 매개변수를 결정해야하므로 장기유출분석이 어렵다. 본 연구의 적용유역으로 미계측유역인 임진강상류 유역에 대한 유출량 추정을 위해 계측 유역의 자료를 활용하여 모형의 매개변수 등을 추정하는 지역화 기법인 다중선형회귀분석과 공간근접분석을 활용하여 유출량을 산정 및 검증하였다. 또한, 확률론적 예측이 가능한 앙상블 기법 적용을 통한 유출량 예측을 하였고, 이를 예측 정확성 평가지표를 통해 효율성 검토를 수행하여 미계측유역의 유출량에 대해 확률론적 예측을 수행하였다. 대표적 지역화 기법의 적용성을 검토한 결과, 계측유역을 통해 다중선형회귀분석과 공간근접분석을 abcd 모형에 적용하였다. 모의유출량을 산정하고 실측 유출량과 비교 분석 결과 모의정확성이 높게 분석되었다. 이와 같은 검증 결과를 토대로 미계측유역의 유출량을 추정하였다. 또한, 지역화 기법을 앙상블 기법에 적용하여 확률론적 유출량 예측의 효율성을 검토하였다. 적용유역과 같은 지류를 포함하고 있는 임진강하류 유역을 대상으로 수행하였다. 검증기간(2013년~2017년) 동안의 월 예측 유출량 앙상블 생성을 위해 과거 강우량와 증발량(1988년~2012년) 자료를 사용하였으며, 지역화 기법을 적용한 abcd 모형을 이용하였다. 예측 유출량의 정확성 평가를 실시하였으며, 정확성이 비교적 높게 분석되었다. 이와 같은 결과를 토대로 미계측유역의 확률론적 유출량을 예측하였다. 따라서, 대표적 지역화 기법을 앙상블 기법에 적용하여 확률론적 유출량을 예측할 경우 보다 정확한 유출량 예측이 가능하다.