• 신재생에너지
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• 제4권4호
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• pp.23-29
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• 2008

Wind farm development project contains high business risks because that a wind farm, which is to be operating for 20 years, has to be designed and assessed only relying on a year or little more in-situ wind data. Accordingly, long-term correction of short-term measurement data is one of most important process in wind resource assessment for project feasibility investigation. This paper shows comparison of general Measure-Correlate-Prediction models and neural network, and presents new method using neural network for increasing prediction accuracy by accommodating multiple reference data. The proposed method would be interim step to complete long-term correction methodology for Korea, complicated Monsoon country where seasonal and diurnal variation of local meteorology is very wide.

• Journal of Positioning, Navigation, and Timing
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• 제8권4호
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• pp.209-214
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• 2019

Precise point positioning (PPP) requires precise orbit and clock products. International GNSS service (IGS) real-time service (RTS) data can be used in real-time for PPP, but it may not be possible to receive these corrections for a short time due to internet or hardware failure. In addition, the time required for IGS to combine RTS data from each analysis center results in a delay of about 30 seconds for the RTS data. Short-term orbit prediction can be possible because it includes the rate of correction, but the clock correction only provides bias. Thus, a short-term prediction model is needed to preidict RTS clock corrections. In this paper, we used a long short-term memory (LSTM) network to predict RTS clock correction for three minutes. The prediction accuracy of the LSTM was compared with that of the polynomial model. After applying the predicted clock corrections to the broadcast ephemeris, we performed PPP and analyzed the positioning accuracy. The LSTM network predicted the clock correction within 2 cm error, and the PPP accuracy is almost the same as received RTS data.

• 한국항만경제학회지
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• 제39권2호
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• pp.129-141
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• 2023

본 연구는 오차교정모형을 활용해 건화물선과 유조선 일간 해상운임의 동태적 특성과 예측 정확도를 분석한다. 공적분된 시계열 자료의 오차를 계산하기 위해 본 연구는 공통 확률적 추세 모형(Common Stochastic Trend Model, CSTM 모형)과 벡터오차교정모형(Vector Error Correction Model, VECM 모형)을 활용한다. 먼저, CSTM 모형의 오차를 사용한 오차교정모형이 VECM 모형의 경우보다 교정계수(adjustment speed coefficient)가 경제학적 이론에 더 부합하는 결과를 보인다. 나아가 조정결정계수(adjR²) 측면에서도 CSTM 모형의 경우가 VECM 모형에 비해 모형 적합도가 큰 것으로 나타난다. 둘째, 예측 정확도를 판단하는 지표인 평균 절대 오차와 평균 절대 척도 오차를 살펴보면, CSTM 모형의 오차를 이용한 모형이 VECM 모형의 오차를 이용한 모형보다 총 15가지 경우 중에 12가지 경우에서 예측 정확도가 높은 것을 확인할 수 있다. 미래 연구주제로서 1) 두 가지 오차를 모두 활용하는 분석 및 예측 과제, 2) 원자재 및 에너지 자원 시장의 데이터를 추가하는 과제, 3) 오차항의 부호에 따라 교정계수를 다르게 추정하는 과제 등을 제시한다.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2010년 춘계학술발표회 논문집
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• pp.429-431
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• 2010

The hybrid geoid model should be determined by fitting the gravimetric geoid to the geometric geoid which were presented the local vertical level. Therefore, it is necessary to find firstly the optimal scheme for improving the accuracy of gravimetric geoid in order to development the high-precision hybrid geoid model. Through finding the optimal scheme for determining the each part of gravimetric geoid, the most accurate gravimetric geoid model in Korea will be developed when the EIGEN-CG03C model to degree 360, 4-band spherical FFT and RTM reduction methods were used for determining the long, middle and short-frequency part of gravimetric geoid respectively. Finally, we developed the hybrid geoid model around Korea by correcting to gravimetric geoid with the correction term. The correction term is modelled using the difference between GPS/Levelling derived geoidal heights and gravimetric geoidal heights. The stochastic model used in the calculation of correction term is the LSC technique based on second-order Markov covariance function. 503 GPS/Levelling data were used to model the correction term. The degree of LSC fitting to the final hybrid geoid model in Korea was evaluated as 0.001m ${\pm}0.054m$.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2000년도 추계 학술발표회 논문집 Proceedings of EESK Conference-Fall 2000
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• pp.73-80
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• 2000

The distance correction term -logA0 of the local magnitude scale was estimated for earthquakes in southern Korea using linear least-squares inversion and interpolation scheme. Total 1054 short-period velocity seismograms from 107 local events recorded at hypocentral distances ranging from 10 to 480 km were used in this study. Simulated Wood-Anderson amplitudes were obtained from velocity seismograms with use of revised Wood-Anderson instrument response with static magnification 2080, damping factor 0.7, and natural period 0.8 sec. The estimated distance correction term for southern Korea is found to be -logA0=1.137 log(r/17) + 0.001159(r-17) + 20, where r is hypocentral distance in kilometers. The attenuation rate of this distance correction term falls between those of southern California and eastern North America.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2008년도 추계학술대회 논문집
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• pp.278-281
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• 2008

In these days the installation of wind turbines or wind parks includes a high financial risk. So for the planning and the constructing of wind farms, long-term data of wind speed and wind direction is required. However, in most cases only few data are available at the designated places. Traditional Measure-Correlate-Predict (MCP) can extend this data by using data of nearby meteorological stations. But also Neural Networks can create such long-term predictions. The key issue of this paper is to demonstrate the possibility and the quality of predictions using Neural Networks. Thereto this paper compares the results of different MCP Models and Neural Networks for creating long-term data with various indexes.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.864-867
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• 2006

Thermal infrared images of Landsat-5 TM and Landsat-7 ETM+ sensors have been unrivalled sources of high resolution thermal remote sensing (60m for ETM+, 120m for TM) for more than two decades. Atmospheric effect that degrades the accuracy of Sea Surface Temperature (SST) measurement significantly, however, can not be corrected as the sensors have only one thermal channel. Recently, MODIS sensor onboard Terra satellite is equipped with dual-thermal channels (31 and 32) of which the difference of at-satellite brightness temperature can provide atmospheric correction with 1km resolution. In this study we corrected the atmospheric effect of Landsat SST by using MODIS data obtained almost simultaneously. As a case study, we produced the Landsat SST near the eastern and western coast of Korea. Then we have obtained Terra/MODIS image of the same area taken approximately 30 minutes later. Atmospheric correction term was calculated by the difference between the MODIS SST (Level 2) and the SST calculated from a single channel (31 of Level 1B). This term with 1km resolution was used for Landsat SST atmospheric correction. Comparison of in situ SST measurements and the corrected Landsat SSTs has shown a significant improvement in $R^2$ from 0.6229 to 0.7779. It is shown that the combination of the high resolution Landsat SST and the Terra/MODIS atmospheric correction can be a routine data production scheme for the thermal remote sensing of ocean.

• 해운물류연구
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• 제34권4호
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• pp.545-563
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• 2018

본 연구의 목적은 VLCC(Very Large Crude Oil Carrier) 운임에 영향을 미치는 주요 결정요인의 장기적 탄성치를 추정하는 것이다. 이를 위해 본 연구는 영국 해운 전문 기업인 클락슨이 공표하는 연간 VLCC 운임을 종속변수로, 원유(Crude oil) 물동량, VLCC 선복량, 벙커유 가격, Libor 금리를 설명변수로 사용하였다. 본 연구는 벡터오차수정모형(Vector Error Correction Model; VECM)을 사용하여 운임 결정 장기균형함수를 추정하였으며, 추정결과 물동량 1.0% 증가 시 운임 6.4% 증가, 선복량 1.0% 증가 시 운임 1.9% 감소, 벙커유 가격 1.0% 증가 시 운임 0.3% 감소, 금리 1.0% 증가 시 운임은 0.18% 증가하는 것으로 나타났다. 벙커유 가격의 경우 일반적인 직관과 반대되는 마이너스(-) 부호로 계수가 추정되었는데, 이는 설명변수 중 벙커유 가격이나 금리 등의 2차 변수가 운임에 미치는 영향력은 적은 반면 직접적인 수급 변수가 운임을 결정하는 주요 요인이기 때문인 것으로 이해된다. 후속연구에서 컨테이너선, 건화물선 등 다른 선종들을 대상으로 연구를 수행하고 다양한 선종별 운임의 결정요인을 비교 분석하는 것이 필요하다.

• 자원ㆍ환경경제연구
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• 제9권2호
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• pp.373-391
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• 2000

This paper investigates the existence of a long-run relationship between world oil price and consumer price index for Korea during 1983~1999. The cointegration and error correction modelling approaches have been applied. Empirical results suggest that there exists a long-run relationship among world oil prices. consumer prices, M2 and a production gap variable. The dynamic behavior of the relationship has been investigated by estimating a error correction model, in which the error correction term have been found significant. The error correction model has also been found to be robust as it satisfy almost all relevant diagnostic tests.

• 대한원격탐사학회지
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• 제25권6호
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• pp.487-499
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• 2009

Atmospheric correction of satellite measurements is a major step to estimate accurate surface reflectance of solar spectrum channels. In this study, Simplified Method for the Atmospheric Correction (SMAC) radiative transfer model used to retrieve surface reflectance from MODIS (MODerate resolution Imaging Spectrometer) top of atmosphere (TOA) reflectance. It is fast and simple atmospheric correction method, so it uses for work site operation in various satellite. This study attempts a test of accuracy of SMAC through a sensitivity test to detected error sources and to improve accuracy of surface reflectance using SMAC. The results of SMAC as compared with MODIS surface reflectance (MOD09) was represented that low accuracy ($R^2\;=\;0.6196$, Root Means Square Error (RMSE) = 0.00031, bias = - 0.0859). Thus sensitivity analysis of input parameters and coefficients was conducted to searching error sources. Among the input parameters, Aerosol Optical Depth (AOD) is the most influence input parameter. In order to modify AOD term in SMAC code, Stepwise multiple regression was performed with testing and remove variable in three stages with independent variables of AOD at 550nm, solar zenith angle, viewing zenith angle. Surface reflectance estimation by using Newly proposed AOD term in the study showed that improve accuracy ($R^2\;=\;0.827$, RMSE = 0.00672, bias = - 0.000762).