• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2003년도 가을 학술발표회 논문집
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• pp.317-324
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• 2003

Kriging interpolation is one of the gennerally used interpolation techniques in Geostatics field. This research refers to the contents about important experimental variogram and the study of theoretical variogram and formulation of Kriging interpolation. Kriging interpolation is applied as interpolation for stress smoothing in finite element method. Posteriori error estimation which makes use of stress smoothing from the FEM is very important part, we try to make practical application of surface regeneration ability from Kriging interpolation. This research is necessary preceding one in order to materialize adaptive FTM through posteriori error estimation. For instance, find the estimate value and estimate the propriety through various theoretical variogram models of the reference analyzed from tensional L-shape domain. It also provides possibility of the Kriging interpolation through comparing to existing Least square method as well.

• 한국국방경영분석학회지
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• 제8권1호
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• pp.99-107
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• 1982

This paper is concerned with the optimality of exponential smoothing applied to the general IMA process with different moving average and differencing orders. Numerical experiments were performed for IMA(m,n) process with various combinations of m and n, and the corresponding forecast errors were compared. Results show that the higher differencing order is more critical to the optimality of exponential smoothing, i.e., the IMA process with the higher moving average order, forecasted by exponential smoothing, has comparatively smaller forecast error. If the difference between the differencing order and the moving average order becomes larger, the accuracy of forecast by exponential smoothing declines gradually.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2003년도 추계학술대회 논문집(III)
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• pp.247-251
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• 2003

The velocity of train which is measured from pulse generator attached to TM is used for displaying or control signal of inverter and so on. Measured signals increase and decrease step-by-step by pulse counting or monotonously by F/V conversion. But noises and signal distortions by measuring error like alias make it difficult to provide correct velocity infomation and estimate the acceleration. In this paper, we investigated the performance of Smoothing method for suppressing the noises in velocity signals. And the difference between Smoothed signal and origin velocity signals is inspected and the comparison with low pass filtering show applicable of Smoothing method for noise rejection and the estimation of signal. Finally, acceleration curves estimated from Smoothing method are compared with real accelerator signal attached to train.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2003년도 추계학술대회논문집
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• pp.159-162
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• 2003

The remeshing algorithm using the constrained Delaunay method adapted to the mesh density map is developed. In the finite element simulation of forging process, the numerical error increases as the process goes on. However, it is not desirable to use a uniformly fine mesh in the whole domain. Therefore, it is necessary to reduce the analysis error by constructing locally fine mesh at the region where the error is concentrated such as die corner. In this paper, the point insertion algorithm is used and mesh size is controlled by using a mesh density map constructed with a posteriori error estimation. And an optimized smoothing technique is adapted to have smooth distribution and improve the quality of the mesh.

• 소성∙가공
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• 제8권3호
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• pp.294-305
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• 1999

A vision-based surface-strain measurement system has been still improved since the authors devel-oped the first version of it. New algorithms for the subpixel measurement and surface smoothing are introduced to improve the accuracy and precision in the present study. The effects of these algorithms are investigated by error analysis. And the equations required to calculate 3D surface-strain of a shell element are derived from the shape function of a linear solid finite-element. The influences of external factors on the measurement error are also examined, and several trials are made to obtain possible optimal condition which may minimize the error.

• 산업경영시스템학회지
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• 제42권1호
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• pp.129-136
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• 2019

In this study, we proposed a model for forecasting power energy demand by investigating how outside temperature at a given time affected power consumption and. To this end, we analyzed the time series of power consumption in terms of the power spectrum and found the periodicities of one day and one week. With these periodicities, we investigated two time series of temperature and power consumption, and found, for a given hour, an approximate linear relation between temperature and power consumption. We adopted an exponential smoothing model to examine the effect of the linearity in forecasting the power demand. In particular, we adjusted the exponential smoothing model by using the variation of power consumption due to temperature change. In this way, the proposed model became a mixture of a time series model and a regression model. We demonstrated that the adjusted model outperformed the exponential smoothing model alone in terms of the mean relative percentage error and the root mean square error in the range of 3%~8% and 4kWh~27kWh, respectively. The results of this study can be used to the energy management system in terms of the effective control of the cross usage of the electric energy together with the outside temperature.

• Journal of the Korean Data and Information Science Society
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• 제28권3호
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• pp.709-720
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• 2017

In healthcare and medical research, many important variables have a measurement error such as body mass index and laboratory data. It is also not easy to collect samples of large size because of high cost and long time required to collect the target patient satisfied with inclusion and exclusion criteria. Beside, the demand for solving a complex scientific problem has highly increased so that a semiparametric regression approach could be of substantial value solving this problem. To address the issues of measurement error, small domain and a scientific complexity, we conduct a multivariable Bayesian smoothing under structural measurement error covariate in this article. Specifically we enhance our previous model by incorporating other useful auxiliary covariates free of measurement error. For the regression spline, we use a radial basis functions with fixed knots for the measurement error covariate. We organize a fully Bayesian approach to fit the model and estimate parameters using Markov chain Monte Carlo. Simulation results represent that the method performs well. We illustrate the results using a national survey data for application.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2004년도 추계학술대회논문집
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• pp.75-78
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• 2004

A mesh generation algorithm adapted to the mesh density map using the Delaunay mesh generation technique is developed. In the finite element analyses of the forging processes, the numerical error increases as the process goes on because of discrete property of the finite elements or severe distortion of elements. Especially, in the region where stresses and strains are concentrated, the numerical discretization error will be highly increased. However, it is too time consuming to use a uniformly fine mesh in the whole domain to reduce the expected numerical error. Therefore, it is necessary to construct locally refined mesh at the region where the error is concentrated such as at the die corner. In this study, the point insertion algorithm is used and the mesh size is controlled by moving nodes to optimized positions according to a mesh density map constructed with a posteriori error estimation. An optimization technique is adopted to obtain a good position of nodes. And optimized smoothing techniques are also adopted to have smooth distribution of the mesh and improve the mesh element quality.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2016년도 춘계학술대회
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• pp.305-307
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• 2016

The purpose of this paper is to determine the optimal values of the gain parameters used in the tracking module for a highly dynamic warship. The algorithm of the tracking module uses the ${\alpha}-{\beta}-{\gamma}$ filter to compute accurate estimates and update the state variables, that is, positions, velocity and acceleration. The filtering coefficients ${\alpha}$, ${\beta}$ and ${\gamma}$ are determined from set values of the damping parameter, ${\xi}$. Optimization is achieved by plotting a range of the damping parameter ${\xi}$ against the corresponding residual error and then selecting the best value of ${\xi}$ with the minimum residual error. Optimal values of the smoothing coefficients are subsequently computed from the selected damping parameter, ${\xi}$.

• Journal of information and communication convergence engineering
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• 제8권3호
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• pp.281-288
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• 2010

This paper investigates the performance of IEEE 802.11p wireless access in vehicular environments (WAVE) system in small-scale fading models reported by Georgia Institute of Technology (Georgia Tech). We redesign the small-scale fading models to be applied to the computer simulation and develop the IEEE 802.11p WAVE physical layer simulator to provide the bit error rate and packet error rate performances. Moreover, a new channel estimator using decision directed channel estimation and linear minimum mean square error smoothing is proposed in order to improve the performance of the conventional least square channel estimator using two identical long training symbols. The simulation results are satisfactorily coincident with the scenarios of Georgia Tech report, and the proposed channel estimator significantly outperforms the conventional channel estimator.