• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.69.2-69
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• 2002

Process measurements contain random and gross errors and the size estimation of gross errors is required for production accounting. Mixed integer programming technique had been applied to identify and estimate the gross errors simultaneously. However, the compensate model based on mixed integer programming used all measured variables or spanning tree as gross error candidates. This makes gross error estimation problem combinatorial or computationally expensive. Mixed integer programming with test statistics is proposed for computationally inexpensive gross error identification /estimation. The gross error candidates are identified by measurement test and the set of gross error candidates are...

• Korean Journal of Construction Engineering and Management
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• v.7 no.4 s.32
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• pp.91-99
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• 2006

The purpose of this study is propose an Artificial Neural Network(ANN) model for the construction estimate of the public educational facility at conceptual stage. The current method for the preliminary cost estimate of the public educational facility uses a single-parameter which is based on basic criteria such as a gross floor area. However, its accuracy is low due to the nature of the method. When the difference between the conceptual estimate and detailed estimate is huge, the project has to be modified to meet the established budget. Thus, the ANN model is developed by using multi-parameters in order to estimate the project budget cost more accurately. The result of the research shows 6.82% of the testing error rates when the developed model was tested. The error rates and the error range of the developed model are smaller than those of the general preliminary estimating model at conceptual stage. Since the proposed ANN model was trained using the detailed estimate information of the past 5 years' school construction data, it is expected to forecast the school project cost accurately.

• Journal of applied mathematics & informatics
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• v.8 no.2
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• pp.327-343
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• 2001

This is a survey article on finite element a posteriori error estimates with an emphasize on gradient recovery type error estimators. As an example, the error estimator based on the ZZ patch recovery technique will be discussed in some detail.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.328-333
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• 1996

In this paper, we propose a new method to estimate robot position without landmark. At first, it is studied to estimate robot state using Markov decision rule. And, a matching method is discussed for estimating current position more accurately under the estimated current state. At second, we combine or fuse the matching method with the POMDP method in order to estimate the position under a dynamically changing environment. Finally we will show that our method can estimate the position precisely and robustly of which error are not cumulated through simulation results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.7
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• pp.891-897
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• 2013

The power system frequency plays an important role in monitoring and controlling the power system. The frequency can be measured through discrete Fourier transform (DFT) coefficients of its positive fundamental frequency. The accuracy of the frequency estimate is severely affected by noise in the power system signal and the leakage effect of the negative fundamental frequency in DFT. This paper proposes a DFT-based frequency estimation algorithm to cope with the noise as well as the leakage effect. In this algorithm, two suitable digital filters are introduced to reduce efficiently frequency estimate error due to the noise. These filters are designed to use a digital bandpass filter and a second-degree integrator. The effectiveness of the proposed algorithm in reduction of frequency estimate error is verified through simulations on noise, harmonics and frequency deviation.

• Journal of the Korean Graphic Arts Communication Society
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• v.16 no.3
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• pp.121-131
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• 1998

The object color does not look same under the different light source. It depends on the surface spectral reflectance and the spectral distribution of light source. Therefore we should find the surface spectral reflectance of object color and the spectral distribution of light source for color reproduction. Using Wiener estimation, we can estimate the spectral reflectance from low dimensional images obtained with multi-band image acquisition system. The kind and the number of imaging filters have the effect on the estimation of the spectral reflectance. Therefore it is important that optimal filters are selected to minimize the error of the result. In this paper, we describe methods to select optimal filters with minimum error between measured and estimated surface spectral reflectance and to estimate surface spectral reflectance of Munsell color chart from six multi-band images by using Wiener estimation.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1887-1890
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• 2003

This paper presents a three-dimensional (3D) head pose estimation algorithm using the stereo image. Given a pair of stereo image, we automatically extract several important facial feature points using the disparity map, the gabor filter and the canny edge detector. To detect the facial feature region , we propose a region dividing method using the disparity map. On the indoor head & shoulder stereo image, a face region has a larger disparity than a background. So we separate a face region from a background by a divergence of disparity. To estimate 3D head pose, we propose a 2D-3D Error Compensated-SVD (EC-SVD) algorithm. We estimate the 3D coordinates of the facial features using the correspondence of a stereo image. We can estimate the head pose of an input image using Error Compensated-SVD (EC-SVD) method. Experimental results show that the proposed method is capable of estimating pose accurately.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.3
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• pp.141-145
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• 1988

This paper reports a new and simple posteriori error estimate method for adaptive finite element mesh genration especially for the magnetic field problems. To estimate local errors, we consider the interelement boundary conditions. Elements which violate much the conditions are considered to have great errors. Magnetic flux density errors are considered as a basis for refinement. This estimator is tested on two dimensional proplems with singular points. The estimated errors are always under estimated but in same order as exact errors, and this algorithm is much simpler and more convenient than other methods. The adaptive mesh gives much better rate of convergence in global errors than the uniform mesh.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.277-280
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• 1993

When the noise is mainly caused by a detector and is statistically independent of the incident radiation, the multiplexing inherent in the Hadamard transform (HT) spectrometer can provide an improved spectrum-estimate. A spectrum-estimate can be further improved when any nonidealities in the system are compensated. In this research, three spectrum-estimation methods for an HT spectrometer having a nonideal mask are discussed in terms of computational efficiency, statistical bias, the sources of error, and the mean-square error associated with a given estimate. In addition, the results obtained from computer simulations are used to verify the theoretical foundation of each method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.3
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• pp.145-153
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• 2015

This study aims to accurately estimate population distribution more specifically than administrative unites using a RK (Regression-Kriging) model. The RK model is the areal interpolation technique that involves linear regression and the Kriging model. In order to estimate a population’s distribution using a sample region, four different models were used, namely; a regression model, RK model, OK (Ordinary Kriging) model and CK (Co-Kriging) model. The results were then compared with each other. Evaluation of the accuracy and validity of evaluation analysis results were the basis RMSE (Root Mean Square Error), MAE (Mean Absolute Error), G statistic and correlation coefficient (ρ). In the sample regions, every statistic value of the RK model showed better results than other models. The results of this comparative study will be useful to estimate a population distribution of the metropolitan areas with high population density