• 대한전기학회논문지:시스템및제어부문D
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• 제51권4호
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• pp.137-143
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• 2002

Because Block Pulse functions are used in a variety of fields such as the analysis and controller design of systems, it is necessary to find the more exact value of the Block Pulse series coefficients. This paper presents a method for the state estimation of the time-invariant linear systems via the improved estimation method for the Block Pulse coefficients by using the Simpson's rule. The proposed method using the Simpson's rule improve the accuracy of the Block Pulse coefficients.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.258-258
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• 2018

In this study, a hydraulic flow model and an error correction model are combined to improve the flood simulation accuracy. First, the hydraulic flow model is calibrated by optimizing the Manning's roughness coefficient that considers spatial and temporal variability. Then, an error correction model were used to correct the systematic errors of the calibrated hydraulic model. The error correction model is developed using Artificial Neural Networks (ANNs) that can estimate the systematic simulation errors of the hydraulic model by considering some state variables as inputs. The input variables are selected using parital mutual information (PMI) technique. It was found that the calibrated hydraulic model can simulate flood water levels with good accuracy. Then, the accuracy of estimated flood levels is improved further by using the error correction model. The method proposed in this study can be used to the flood control and water resources management as it can provide accurate water level eatimation.