• Proceedings of the KIEE Conference
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• 2007.11b
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• pp.29-30
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• 2007

본 논문은 특수일 전력 수요 예측을 위해 온도 효과를 고려한 데이터 추출법을 이용하여 특수일 전력 수용 예측 오차율을 감소시키는 방법을 제시한다. 제안된 기법의 타당성을 확인하기 위해 논문에서는 통계학에서 사용되는 결정계수를 이용한다. 결정계수를 이용하여 온도효과의 고려 여부가 오차율에 미치는 영향을 분석하였다. 또한 제안된 기법은 1996년 특수일 오차율을 기존 논문의 결과와 비교 분석하여 기존 방식 대비 특수일 전력 수요예측 관련 우수성을 보였으며, 최근 데이터인 2006년 특수일 전력 수요 예측을 통하여 검증하였다.

• The Journal of the Acoustical Society of Korea
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• v.3 no.2
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• pp.46-58
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• 1984

본 논문은 한국어 음성 인식을 위한 유성음, 무성음, 묵음 식별에 관한 연구이다. 주어진 음성 구간을 3가지 음성 신호 부류로 식별하기 위하여 패턴 인식 방법을 사용하였다. 여기에 사용한 분석 파 라메타는 음성 신호의 영교차율, 대수 에너지, 정규화 된 첫 번째 자동 상관 계수, 선형 예측 분석에서 얻은 첫 번째 예측 계수, 그리고 예측 오차의 에너지이다. 한편 측정된 파라메타들이 다차원 가우스 확 률 밀도 함수에 따라 분산되었다는 가정하에서 어어진 최소 거리 법칙에 기본을 두고 음성 구간을 결정 하였다. 측정된 파라메타들을 여러 가지 방법으로 조합하여 식별한 결과 영교차율, 첫 번째 예측계수, 예측 오차의 에너지를 측정 파라메타로 사용했을 때 1%보다 적은 식별 오차율을 얻었다.

• Korean Journal of Food Science and Technology
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• v.24 no.5
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• pp.408-413
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• 1992

This study was conducted to determine the effect of the homogenizing grade of sample on absorbance of near infrared reflectance spectrophotometer with which chemical compositions of food were rapidly and effectively analyzed. By the mathematical treatment of absorbance values standard error of prediction was reduced as follows. 1. The absorbance values of various samples ground for the same periods of time were calibrated before or after treatment with first or second derivative in an attempt to accurately predict the components of samples ground for the different periods of time. The standard error of prediction for moisture content were 1.478%, 0.658% and 0.580%, respectively, those for fat content 0.949%, 0.637% and 0.527%, respectively, and those for protein content 0.514%, 0.493% and 0.394%, respectively. Calibration of absorbance values after second derivative treatment showed the highest accuracy in predicting sample components. 2. The absorbance values of various samples ground for the different periods of time were calibrated before or after treatment with first or second derivative in order to accurately predict the components of samples ground for the different periods of time. The standard error of prediction for moisture content were 1.026%, 0.589% and 0.568%, respectively, and those for protein content 0.860%, 0.557% and 0.399%, respectively. The standard error of prediction were lower in the order of calibrations before and after first and second derivative treatments. As a result, calibration of absorbance values after second derivative treatment showed higher accuracy regardless of grinding time of samples.

• Journal of Astronomy and Space Sciences
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• v.15 no.2
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• pp.437-447
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• 1998

Orbit error analysis was performed for the GPS navigation solutions and ground station tracking data of the KOMPSAT (Korea Multi-Purpose SATellite), which will be launched in 1999 for cartography of Korean peninsula as main mission. A least square method was used for the orbit determination and prediction error simulation including tracking data noises and dynamic modeling errors. It was found that a short-term periodic orbit determination error was caused by the tracking data noise and dominant orbit prediction error was caused by solar flux uncertainty.

• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.589-599
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• 2014

This paper analyzes the forecasting errors of traffic volumes by comparing forecasted volumes for the opening year with the observed ones in the years after the urban railway construction in the metropolitan areas. The result shows that the average inaccuracy of traffic volumes for each station was estimated at around 7.27. Based on the confirmed factors of demand estimation errors, this study seeks for an alternative method to reduce estimation errors in feasibility studies. It is noted that there is a tendency that the inaccuracy varies by regions and the longer construction period or the shorter station spacing is, the overestimation increases. If urban railway projects are proceeded as planed, therefore, the level of the inaccuracy for traffic volume forecast will be decreased. In addition, thanks to the theoretical progress, recent estimation results show higher accuracy than before. In that sense, when we introduce the new railway line, it is necessary to make an accurate and realistic demand forecast based on actual outcomes and tendency of the previous estimation. The limitation of our study is that we only cover the errors of the initial period, the opening year and deal with the exogenous variables. Further research including other variables which might be considered to cause overestimation or errors would be needed for increasing the estimation accuracy of traffic volumes.

• Journal of Navigation and Port Research
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• v.28 no.6
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• pp.509-515
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• 2004

The aim of this paper is to forecast passenger numbers and freight volumes in 2005 and it is proposed optimal tonnage of passenger ship. The forecasting of passenger numbers and freight volumes is important problem in order to determine optimal tonnage of passenger ship, port plan and development. In this paper, the forecasting of passenger numbers and freight volumes are performed by the method of neural network using back-propagation learning algorithm. And this paper compares the forecasting performance of neural networks with moving average method and exponential smooth method As the result of analysis. The forecasting of passenger numbers and freight volumes is that the neural networks performed better than moving average method and exponential smoothing method on the basis of MSE(mean square error) and MAE(mean absolute error).

• Journal of the Korean earth science society
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• v.39 no.3
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• pp.211-227
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• 2018

This study evaluates the prediction skills of stratospheric polar vortex intensification events (VIEs) in Global Seasonal Forecasting System (GloSea5) model, an operational subseasonal-to-seasonal (S2S) prediction model of Korea Meteorological Administration (KMA). The results show that the prediction limits of VIEs, diagnosed with anomaly correlation coefficient (ACC) and mean squared skill score (MSSS), are 13.6 days and 18.5 days, respectively. These prediction limits are mainly determined by the eddy error, especially the large-scale eddy phase error from the eddies with the zonal wavenumber 1. This might imply that better prediction skills for VIEs can be obtained by improving the model performance in simulating the phase of planetary scale eddy. The stratospheric prediction skills, on the other hand, tend to not affect the tropospheric prediction skills in the analyzed cases. This result may indicate that stratosphere-troposphere dynamic coupling associated with VIEs might not be well predicted by GloSea5 model. However, it is possible that the coupling process, even if well predicted by the model, cannot be recognized by monotonic analyses, because intrinsic modes in the troposphere often have larger variability compared to the stratospheric impact.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.638-639
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• 2011

전력수요는 여러 가지 사회, 경제, 기상 등의 복합적인 요인에 의해 결정되므로 예측하기 쉽지 않다. 수요 예측 시스템을 통해 예측된 결과는 예측일의 상황에 맞는 여러 가지 예측과 관련된 변동 요인의 적용범위가 수치적으로 달라 질 수 있어 예측 데이터와 실제 수요와의 오차율이 높아질 수 있다. 따라서 전력수요 실적과 예측간 오차에 영향을 주는 변동 요인의 영향력을 분석하고, 예측일의 상황에 맞게 적절한 수치의 변수를 예측 시스템에 제공하여 예측의 정확성을 향상시키는 방안에 대하여 알아보았다.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.08a
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• pp.99-104
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• 1998

한국어의 자연스러운 음성합성을 위해 280문장에 대하여 남성화자 1명이 발성한 문음성 데이터를 음운 세그먼트, 음운 라벨링, 음운별 품사 태깅하여 음성 코퍼스를 구축하였다. 이 문 음성 코퍼스를 사용하여 음운환경, 품사 뿐만 아니라 구문 구조에 이하여 음운으 lwlthrtlrks이 어떻게 변화하는가에 대하여 xhdrPwjrdfmh 분석하였다. 음운 지속시간을 보다 정교하게 예측하기 위하여, 각 음운의 고유 지속시간의 영향이 배제된 정규화 음운지속시간을 회귀트리를 이용하여 모델화하였다. 평가결과, 기존의 회귀트리를 이용한 음운지속시간 모델에 의한 예측오차는 87%정도가 20ms 이내 이었지만, 정규화 음운 지속시간 모델에 의한 예측 오차는 89% 정도가 20ms 이내로 더욱 정교하게 예측되었다.

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.296-297
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• 2018

본 논문은 3상 T-type 3-레벨 인버터의 모델예측제어에 관한 연구이다. 모델예측제어는 시스템의 모델링을 통한 최적의 성능을 제공하는 제어기법으로 PI 제어보다 빠른 동특성을 갖지만, 정확한 파라미터 값이 요구된다. 본 논문에서는 시스템 파라미터 오차가 3상 T-type 3-레벨 인버터의 예측제어에서 어떤 영향을 주는지 알아보고 출력 파형을 분석한다.