• Journal of the Korean Statistical Society
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• v.22 no.1
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• pp.113-124
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• 1993

In this paper we show that the results of Ahn and Cho (1992) can be applied to a more general class of seasonal models, especially models with autocorrelated errors. Employing the idea of the "two-step estimation" method, we provide test statistics which are easy to compute and have the same asymptotic properties as those in Ahn and Cho (1992) for seasonal unit roots. A numerical example is presented to illustrate the methods and concepts. The power of the test statistics for finite samples is examined through a Monte Carlo sampling experiment.xperiment.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.625-636
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• 2013

In this paper we study four kernel machines for estimating expected shortfall, which are constructed through combinations of support vector quantile regression (SVQR), restricted SVQR (RSVQR), least squares support vector machine (LS-SVM) and support vector expectile regression (SVER). These kernel machines have obvious advantages such that they achieve nonlinear model but they do not require the explicit form of nonlinear mapping function. Moreover they need no assumption about the underlying probability distribution of errors. Through numerical studies on two artificial an two real data sets we show their effectiveness on the estimation performance at various confidence levels.

• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.138-146
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• 2007

The analysis and design method for achieving robust stabilization of Decentralized Dynamic Surface Control (DDSC) is presented for a class of interconnected nonlinear systems. While a centralized design approach of DSC was developed in [1], the decentralized approach to deal with large-scale interconnected systems is proposed under the assumption that interconnected functions among subsystems are unknown but bounded. To provide a closed-loop form with provable stability properties, augmented error dynamics for N nonlinear subsystems with DDSC are derived. Then, the reachable set for errors of the closed-loop systems will be approximated numerically in the form of an ellipsoid in the framework of convex optimization. Finally, a numerical algorithm to calculate the $L_2$ gain of the augmented error dynamics is presented.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.27-32
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• 2003

Atmospheric and oceanic numerical models are usually initial-value and/or boundary-value problems. Change in either initial or boundary conditions leads to a variation of model solutions. Much of the predictability research has been done on the response of model behavior to an initial value perturbation. Less effort has been made on the response of model behavior to a boundary value perturbation. In this study, we use the latest version of the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM3) to study the model uncertainty to tiny SST errors. The results show the urgency to investigate the second kind predictability problem for the climate models.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.203-205
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• 1997

In this paper, we present a useful method of estimating earth resistivity using BP algorithm in Neural-Networks. From this method, equivalent earth resistivity(EER) can be obtained directly using training data composed of field-measured apparent resistivity and probe distance. This approach can reduce errors which is conventionally raised from manual operation of calculating EER. To evaluate its accuracy and convenience, the result of proposed method is compared to that of conventional methods, graphical($\rho$-a graph) and numerical(CDEGS program), respectively.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.7
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• pp.859-866
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• 2003

The Lagrangian dispserion of fluid particles in inhomogeneous turbulence is investigated by a direct numerical simulation of turbulent channel flow. Fluid particle velocity and acceleration along a particle trajectory are computed by employing several interpolation schemes such as linear interpolation, high-order Lagrange polynomial interpolation and the Hermite interpolation schemes. The performances of the schemes are evaluated through comparison of errors in computed particle positions, velocities and accelerations against spectral interpolation. Adopting the four-point Hermite interpolation in the homogeneous directions and Chebyshev polynomials in the wall-normal direction appears to produce most reliable Lagrangian statistics including acceleration correlations with a reasonable amount of computational overhead.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.597-602
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• 2008

Most of structural analyses are concerned with the deformation and stress in a body subjected to external loads. In many fields, however, the interpretation of inverse problems is needed to determine surface tractions or internal stresses. In this study, the inverse processes by using the finite elements and the boundary elements are formulated for the evaluation of internal residual stresses from displacements measured on a remote surface. Small errors in the measured displacements often result in a substantial loss of accuracy of an inverse system. We use the Tikhonov regularization techniques to regularize the ill-conditioned system. Advantages and disadvantages are discussed through numerical examples.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1882-1887
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• 2003

The response surface method (RSM) became one of famous meta modeling techniques, however its approximation errors give designers several restrictions. Classical RSM uses the least squares method (LSM) to find the best fitting approximation models from the all given data. This paper discusses how to construct RSM efficiently and accurately using moving least squares method (MLSM) with sensitivity information. In this method, several parameters should be determined during the construction of RSM. Parametric study and optimization for these parameters are performed. Several difficulties during approximation processes are described and numerical examples are demonstrated to verify the efficiency of this method.

• Proceedings of the KIEE Conference
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• 2002.11d
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• pp.97-99
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• 2002

3D Equivalent magnetic Circuit Network Method (EMCNM) is comparatively the easy way that analyzes 3D models of Electric Machine by using permeance as a distributive magnetic circuit parameter under the existing magnetic equivalent circuit method and Numerical Method. The existing 3D EMCNM could not correctly describe the shape of an analysis target when using rectangular shape element or fan shape element, so it made errors when calculating permeance. Therefore, this paper use the trapezoidal element contained rectangular element. This paper calculate the torque based on the maxwell stress tenser method when the airgap is one layer, three layers, and 5 layers, respectively.

• Korean System Dynamics Review
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• v.10 no.1
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• pp.33-60
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• 2009

This study explores the limitation in making a causal model through an existing case and proposes an alternative plan to improve a theoretical system of causation modeling. To make a dynamic and actual model, several principles are needed such as reality based analysis of system structures and dynamics, consistent expression of causations, conversion of numerical formulas to causal relations, classification and arrangement of variables by size of concept, etc. However, it is hard to find cases to apply these considerations from existing models in System Dynamics. Therefore, this study verifies errors of derived models from literatures and proposes principles and guides that should be considered to make a sound dynamic model on a causal map. It contributes to making an opportunity for exciting public opinion to improve theory about causal maps, yet it has limitation that the study does not advance forward to the experimental step. For future study, it plans to make up by classifying and leveling causal variables, developing a dynamic BSC model.