• 전력전자학회논문지
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• 제11권5호
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• pp.426-430
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• 2006

본 논문에서는 제어 시지연을 갖는 고성능 PI 전류제어기에 대한 새로운 예측전류 적용방법을 모색한다. 먼저 선형 영구자석 동기전동기를 사용한 선형 서보 제어시스템에 존재하는 불가피한 전류예측 오차원인을 분석하고, 전류예측 오차와 제어 시지연을 고려한 전류제어 성능 개선 방법으로 수정된 동기좌표계 비간섭 PI 전류제어기를 제안한다. 그리고 시뮬레이션 및 실험 결과를 통하여 제안된 전류제어기가 서보 제어시스템에 존재하는 전류예측 오차와 제어 시지연이 있는 경우에도 개선된 전류제어응답을 보임을 검증하였다.

• 품질경영학회지
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• 제47권4호
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• pp.783-793
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• 2019

Purpose: The purpose of this study is to apply the machine and deep learning methodology on error terms which are continuously auto-generated on the sensors with specific time period and prove the improvement effects of power generator prediction diagnosis system by comparing detection ability. Methods: The SVM(Support Vector Machine) and MLP(Multi Layer Perception) learning procedures were applied for predicting the target values and sequentially producing the error terms for confirming the detection improvement effects of suggested application. For checking the effectiveness of suggested procedures, several detection methodologies such as Cusum and EWMA were used for the comparison. Results: The statistical analysis result shows that without noticing the sequential trivial changes on current diagnosis system, suggested approach based on the error term diagnosis is sensing the changes in the very early stages. Conclusion: Using pattern of error terms as a diagnosis tool for the safety control process with SVM and MLP learning procedure, unusual symptoms could be detected earlier than current prediction system. By combining the suggested error term management methodology with current process seems to be meaningful for sustainable safety condition by early detecting the symptoms.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제9권4호
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• pp.327-332
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• 2009

This paper proposes a method to improve the accuracy of a short-term electrical load forecasting (STLF) system based on neuro-fuzzy models. The proposed method compensates load forecasts based on the error obtained during the previous prediction. The basic idea behind this approach is that the error of the current prediction is highly correlated with that of the previous prediction. This simple compensation scheme using error information drastically improves the performance of the STLF based on neuro-fuzzy models. The viability of the proposed method is demonstrated through the simulation studies performed on the load data collected by Korea Electric Power Corporation (KEPCO) in 1996 and 1997.

• Journal of the Korean Data and Information Science Society
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• 제16권4호
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• pp.999-1012
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• 2005

We compare two popular algorithms in current machine learning and statistical learning areas, boosting method represented by AdaBoost and kernel based SVM (Support Vector Machine) using 13 real data sets. This comparative study shows that boosting method has smaller prediction error in data with heavy noise, whereas SVM has smaller prediction error in the data with little noise.

• International Journal of Ocean System Engineering
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• 제3권3호
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• pp.116-130
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• 2013

The prediction of ocean currents in real time over the warning times of a few hours or days is required in planning many operation-related activities in the ocean. Traditionally this is done through numerical models which are targeted toward producing spatially distributed information. This paper discusses a complementary method to do so when site-specific predictions are desired. It is based on the use of a recurrent type of neural network as well as the statistical tool of model tree. The measurements made at a site in Indian Ocean over a period of 4 years were used. The predictions were made over 72 time steps in advance. The models developed were found to be fairly accurate in terms of the selected error statistics. Among the two modeling techniques the model tree performed better showing the necessity of using distributed models for different sub-domains of data rather than a unique one over the entire input domain. Typically such predictions were associated with average errors of less than 2.0 cm/s. Although the prediction accuracy declined over longer intervals, it was still very satisfactory in terms of theselected error criteria. Similarly prediction of extreme values matched with that of the rest of predictions. Unlike past studies both east-west and north-south current components were predicted fairly well.

• Journal of Electrical Engineering and information Science
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• 제2권6호
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• pp.138-145
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• 1997

This paper proposes an adaptive algorithm for the quantization step size control of MPEG-2, using the information obtained from the previously encoded picture. Before quantizing the DCT coefficients, the properties of reconstruction error of each macro block (MB) is predicted from the previous frame. For the prediction of the error of current MB, a block with the size of MB in the previous frame are chosen by use of the motion vector. Since the original and reconstructed images of the previous frame are available in the encoder, we can calculate the reconstruction error of this block. This error is considered as the expected error of the current MB if it is quantized with the same step size and bit rate. Comparing the error of the MB with the average of overall MBs, if it is larger than the average, small step size is given for this MB, and vice versa. As a result, the error distribution of the MB is more concentrated to the average, giving low variance and improved image quality. Especially for the low bit application, the proposed algorithm gives much smaller error variance and higher PSNR compared to TM5 (test model 5).

• Nuclear Engineering and Technology
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• 제44권4호
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• pp.355-362
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• 2012

The aim of this study was to develop a bundle position-wise linear model (BPLM) to predict Pressure Tube (PT) diametral creep employing the previously measured PT diameters and operating conditions. There are twelve bundles in a fuel channel, and for each bundle a linear model was developed by using the dependent variables, such as the fast neutron fluences and the bundle coolant temperatures. The training data set was selected using the subtractive clustering method. The data of 39 channels that consist of 80 percent of a total of 49 measured channels from Units 2, 3, and 4 of the Wolsung nuclear plant in Korea were used to develop the BPLM. The data from the remaining 10 channels were used to test the developed BPLM. The BPLM was optimized by the maximum likelihood estimation method. The developed BPLM to predict PT diametral creep was verified using the operating data gathered from Units 2, 3, and 4. Two error components for the BPLM, which are the epistemic error and the aleatory error, were generated. The diametral creep prediction and two error components will be used for the generation of the regional overpower trip setpoint at the corresponding effective full power days. The root mean square (RMS) errors were also generated and compared to those from the current prediction method. The RMS errors were found to be less than the previous errors.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권7호
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• pp.423-427
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• 2005

In this paper, we proposed a new ARMA model identification which estimate the parameters to make the current prediction error uncorrelated with the past one. As good properties of the proposed method, we show the uniqueness, consistency of the estimate and asymptotic normality of the estimation error. Via simulation results, we show that the proposed method give good estimates for various systems which have different power spectrum. Moreover, the estimation of gyroscope random errors shows that the proposed method is applicable to the real data.

• 소성∙가공
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• 제23권7호
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• pp.446-452
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• 2014

In the current study finite element forming analysis is performed to understand the final geometric accuracy limitations for the stamping of an automotive S-rail from four different steel sheets having tensile strengths of 340MPa, 440MPa, 590MPa and 780MPa. Comparisons between the analysis and the experiments for both springback and formability as measured by the amount of edge draw-in and the thickness distribution were conducted. The springback modes were classified according to a scheme proposed in the current investigation and the error was calculated using the normalized root mean square error method. While the analysis results show fairly good agreement with the experimental data for deformation and formability, the simulation accuracy is lower for predicting wall curl, camber and section twist as the UTS of steel sheet increases.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -1
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• pp.599-602
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• 2002

A new approach of error concealment using a digital watermarking technique for interframe video coding is presented in this paper. In the proposed method, the most important feature of the reference frame is extracted. Then, this feature is embedded into the prediction error of current frame prior to transmission. Error concealment is achieved by means of recovering the erroneous reference frame using the embedded data before the reconstruction of current frame is performed. Simulation results demonstrated the effectiveness of the proposed method.