• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.25-25
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• 2023

The ensemble optimal interpolation (EnOI) scheme is a sub-optimal alternative to the ensemble Kalman filter (EnKF) with a reduced computational demand making it potentially more suitable for operational applications. Since only one model is integrated forward instead of an ensemble of model realizations, online estimation of the background error covariance matrix is not possible in the EnOI scheme. In this study, we investigate two Gaussian noise based ensemble generation strategies to produce dynamic covariance matrices for assimilation of water level observations into a distributed hydrological model. In the first approach, spatially correlated noise, sampled from a normal distribution with a fixed fractional error parameter (which controls its standard deviation), is added to the model forecast state vector to prepare the ensembles. In the second method, we use an adaptive error estimation technique based on the innovation diagnostics to estimate this error parameter within the assimilation framework. The results from a real and a set of synthetic experiments indicate that the EnOI scheme can provide better results when an optimal EnKF is not identified, but performs worse than the ensemble filter when the true error characteristics are known. Furthermore, while the adaptive approach is able to reduce the sensitivity to the fractional error parameter affecting the first (non-adaptive) approach, results are usually worse at ungauged locations with the former.

• Journal of Electrical Engineering and Technology
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• 제13권2호
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• pp.981-988
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• 2018

In order to acquire an accurate TOF, this paper proposes a method that produces TOF by using a mathematical model for the envelope of the received signal obtained from a system dynamic model of ultrasonic transducer. The proposed method estimates the arrival time of the received signal retrospectively by comparing its wave form obtained after triggering point with its mathematical envelope model. Experimental result shows that the error due to variation of triggering point can be dramatically decreased by implementing the proposed method.

• 대한전기학회논문지
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• 제43권5호
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• pp.838-847
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• 1994

Although there is an analytical proof of modeling capability of the neural network, the convergency error in nonlinearity modeling is inevitable, since the steepest descent based practical larning algorithms do not guarantee the convergency of modeling error. Therefore, it is difficult to apply the neural network to control system in critical environments under an on-line learning scheme. Although the convergency of modeling error of a neural network is not guatranteed in the practical learning algorithms, the convergency, or boundedness of tracking error of the control system can be achieved if a proper feedback control law is combined with the neural network model to solve the problem of modeling error. In this paper, the neural network is introduced for compensating a system uncertainty to control a nonlinear dynamic system. And for suppressing inevitable modeling error of the neural network, an iterative neural network learning control algorithm is proposed as a virtual on-line realization of the Adaptive Variable Structure Controller. The efficiency of the proposed control scheme is verified from computer simulation on dynamics control of a 2 link robot manipulator.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2009년도 춘계학술대회 논문집
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• pp.1557-1565
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• 2009

According to the GM/RT2141, to assess the safety of vehicle, the validated the vehicle dynamic model should be applied. The validation of the vehicle model is against the static test, some kind of vehicle type test results have been used to determine the suspension characteristics and the vehicle dynamic characteristics. To validate the vehicle model and the test results, first the test results has been analysed as to specified the suspension characteristics and than the parameters to related with the test result has to be adjusted to show the same results of the test. In this process the parameters of vehicle model have been determined to show the coherence of the two results of the simulation and the test by trial & error. In this report, the optimization tool has been introduced in this model validation process and shows the efficient and well validated model.

• 센서학회지
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• 제13권1호
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• pp.1-11
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• 2004

Due to various types of errors added to dynamic weight measurement data, proper methods to reduce measurement errors are required to produce reliable weights. To cope with parasitic types of errors in real systems, information provided by the various sensors is utilized and combined in such a way to reduce the measurement errors of load cells. In addition to four channels of load cells from a trailer, an accelerometer is used to obtain the information to compensate the error induced from vertical movement of the vehicle due to the variation of ground level. A model trailer system is run to verify the effectiveness of the proposed method to reduce noise of dynamic weight measurements. Experiments show that the processed error magnitudes of less than 20 g can be obtained for 10 Kg experimental loads.

• The Journal of Asian Finance, Economics and Business
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• 제7권1호
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• pp.37-46
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• 2020

The paper examines the dynamic relationship of domestic credit and stock market liquidity on the economic growth of the Philippines from 1995 to 2018 applying the autoregressive distributed lag (ARDL) bounds testing approach to cointegration, together with Granger causality test based on vector error correction model (VECM). The ARDL model indicated a long-run relationship of domestic credit and stock market liquidity on GDP growth. When the GDP per capita is the dependent variable there is weak cointegration. Also, the Johansen cointegration test confirmed the existence of long-run relationship of domestic credit and stock market liquidity both on GDP growth and GDP per capita. The VECM concludes a long-run causality running from domestic credit and stock market liquidity to GDP growth. At levels, domestic credit has significant short-run causal relationship with GDP growth. As for stock market liquidity at first lag, has significant short-run causal relationship with GDP growth. With regards to VECM for GDP per capita, domestic credit and stock market liquidity indicates no significant dynamic adjustment to a new equilibrium if a disturbance occurs in the whole system. At levels, the results indicated the presence of short-run causality from stock market liquidity and GDP per capita. The CUSUMSQ plot complements the findings of the CUSUM plot that the estimated models for GDP growth and GDP per capita were stable.

• 대한기계학회논문집
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• 제13권1호
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• pp.29-39
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• 1989

본 논문에서는 우선 밸브 기구의 동적 특성을 보다 정교하게 묘사하기 위해서 4 자유도 집중 질량 모델을 세우고 시뮬레이션 결과와 실험 결과를 비교하여 실험을 더 잘 묘사할 수 있도록 모델을 개선하였다. 그리고 수립된 모델을 사용하여 밸브 변위, 속도, 가속도 특성 및 밸브 기구의 작동 오차를 정의하였다. 이 평균 자승 오차를 최소함으로써 중어진 캠 변위는 크게 변화시키지 않으면서 가속도 및 속도를 최소화한 캠을 설계하였다.

• 정보처리학회논문지C
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• 제12C권4호
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• pp.519-524
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• 2005

동하중 측정 데이터에 추가되는 여러 가지 종류의 오차로 인하여, 신뢰할 수 있는 하중을 구하기 위해 측정 오차를 감소시키는 적절한 방법이 필요하다. 과도한 진동으로 인해 발생하는 측정 오류는 쉽게 제거하기 어렵다. 이러한 오류를 최소화하기 위하여 측정 장치 혹은 측정 대상의 수직 운동과 상호 관계가 전혀 없는 광 센서 시스템을 이용한다. 여러 가지 시료들의 흐름률을 광 센서를 이용하여 측정함으로써 로드셀을 이용한 부정확한 측정 부분을 보완한다. 동하중 측정시 발생하는 잡음 감소를 확인하기 위하여 모형 트레일러 시스템을 사용하며, 제안된 방법이 효과적임을 확인한다.

• 자원ㆍ환경경제연구
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• 제12권2호
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• pp.327-346
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• 2003

본고는 에너지소비와 경제성장의 관계를 밝히는 데 목적을 둔다. 먼저 에너지 소비, 물가, 실질소득으로 구성된 모형이 안정적임을 확인한 후, 오차수정모형을 이용하여 단기에 있어서 에너지 소비와 소득이 상호 영향을 미쳐 쌍방적 인과관계가 존재함을 보인다. 이와 더불어 예측오차의 분산분해와 충격반응함수를 도입하여 경제성장이 에너지소비를 증가시키나, 에너지소비증가가 경제성장에 미치는 효과는 단기적일 뿐 아니라 물가에 비교적 오랫동안 영향을 미친다는 것을 밝힌다. 이러한 사실은 우리나라의 경우 경제성장으로 에너지 소비가 증가하나, 증가한 에너지 소비가 인플레 등을 통해 경제성장의 장애요인으로 작용할 수 있음을 의미한다.

• International Journal of Control, Automation, and Systems
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• 제6권6호
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• pp.948-953
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• 2008

In high dynamic situations, the GPS carrier tracking loop requires a wide bandwidth to track a carrier signal because the Doppler frequency changes more rapidly with time. However, a wide bandwidth allows noises within the bandwidth of the tracking loop to pass through the loop filter. As these noises are used in the numerical controlled oscillator(NCO), the carrier tracking loop of a GPS receiver shows a degraded performance in high dynamic situations. To solve this problem, an adaptive two-stage Kalman filter, which offers the NCO a less noisy phase error, can be used. This filter is based on a carrier phase dynamic model and can adapt to an incomplete dynamic model and a quickly changed Doppler frequency. The performance of the proposed tracking loop is verified by several simulations.