• Bulletin of the Korean Mathematical Society
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• v.55 no.4
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• pp.1303-1315
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• 2018

For principal component analysis (PCA) to efficiently analyze large scale matrices, it is crucial to find a few singular vectors in cheaper computational cost and under lower memory requirement. To compute those in a fast and robust way, we propose a new stochastic method. Especially, we adopt the stochastic variance reduced gradient (SVRG) method [11] to avoid asymptotically slow convergence in stochastic gradient descent methods. For that purpose, we reformulate the PCA problem as a unconstrained optimization problem using a quadratic penalty. In general, increasing the penalty parameter to infinity is needed for the equivalence of the two problems. However, in this case, exact penalization is guaranteed by applying the analysis in [24]. We establish the convergence rate of the proposed method to a stationary point and numerical experiments illustrate the validity and efficiency of the proposed method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.11
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• pp.15-23
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• 2005

In this paper, the static and dynamic behavior of partly wrinkled membrane was studied. Membrane finite elements were used in the analysis and the wrinkling in the element was accounted for by a penalty-parameter material modeling which was implemented as a user subroutine to ABAQUS. The wrinkle algorithm was applied to a corner-loaded square membrane to investigate the effect of wrinkling on the static and dynamic behavior.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.9
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• pp.48-55
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• 2005

In this paper, wrinkling behavior for anisotropic membrane was studied. The analyses were done by using membrane elements and the wrinkling was accounted for by the penalty parameter modified material modeling which was implemented to ABAQUS as a user subroutine. The wrinkle model was applied to corner-loaded square membranes in which the effect of the diameter of steel pin, edge cut-off length and the magnitude of shear moduli on the wrinkling was investigated.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.11
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• pp.747-752
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• 2004

This paper presents an iterative linear matrix inequality (LMI) approach to the design of a static output feedback (SOF) stabilization controller. A linear penalty function is incorporated into the objective function for the non-convex rank constraint so that minimizing the penalized objective function subject to LMIs amounts to a convex optimization problem. Hence, the overall procedure results in solving a series of semidefinite programs (SDPs). With an increasing sequence of the penalty parameter, the solution of the penalized optimization problem moves towards the feasible region of the original non-convex problem. The proposed algorithm is, therefore, convergent. Extensive numerical experiments are Deformed to illustrate the proposed algorithm.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.12
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• pp.655-660
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• 2004

This paper deals with the design of a fixed-structure $H_\infty$ power system stabilizer (PSS) by using an iterative linear matrix inequality (LMI) method. The fixed-structure $H_\infty$ controller is represented in terms of LMIs with a rank condition. To solve the non-convex rank-constrained LMI problem, a linear penalty function is incorporated into the objective function so that minimizing the penalized objective function subject to LMIs amounts to a convex optimization problem. With an increasing sequence of the penalty parameter, the solution of the penalized optimization problem moves towards the feasible region of the original non-convex problem. The proposed algorithm is, therefore, convergent. Numerical experiments show the practical applicability of the proposed algorithm.

• Nuclear Engineering and Technology
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• v.28 no.3
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• pp.331-338
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• 1996

In the thermal-hydraulic design, the effect of fuel rod bow is quantified tv the rod bow DNBR penalty which is a key design parameter to assure the coolability of fuel assembly in the pressurized water reactor. In this work, a computer program for the evaluation of the rod bow DNBR penalty based on Westinghouse methodology is developed and its application procedure is proposed. The computer simulation is based on the Monte-Carlo method. The qualification of developed computer program is performed by a comparison of calculational result with that given by Westinghouse's document. A new application procedure is built using batch mean and batch standard deviation. The normality of sample population generated by the batch calculation is confirmed by means of a chi-square test for goodness of fit. On the view point of statistics it is effected that the more reliable design value may be produced by the new application procedure.

• Geophysics and Geophysical Exploration
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• v.9 no.4
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• pp.299-303
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• 2006

Geologic noise, especially located at shallow depth, can be a great obstacle in the interpretation of geophysical data. Thus, it is important to suppress geologic noise in order to accurately detect major anomalous bodies in the survey area. In the inversion of geophysical data, model parameters at shallow depth, which have small size and low contrast of physical property, can be regarded as one of geologic noise. The least-squares method with smoothness constraint has been widely used in the inversion of geophysical data. The method imposes a big penalty on the large model parameter, while a small penalty on the small model parameter. Therefore, it is not easy to suppress small anomalous boies. In this study, we developed a new inversion scheme which can effectively suppress geologic noise by imposing a big penalty on the slowly varying model parameter and a small penalty on the largely varying model parameter. We call the method MTE (main-target emphasizing) inversion. Applying the method to the inversion of 2.5D small loop EM data, we can ensure that it is effective in suppressing small anomalous boies and emphasizing major anomalous bodies in the survey area.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.493-505
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• 2017

Maximum likelihood estimation (MLE) of the generalized extreme value distribution (GEVD) is known to sometimes over-estimate the positive value of the shape parameter for the small sample size. The maximum penalized likelihood estimation (MPLE) with Beta penalty function was proposed by some researchers to overcome this problem. But the determination of the hyperparameters (HP) in Beta penalty function is still an issue. This paper presents some data adaptive methods to select the HP of Beta penalty function in the MPLE framework. The idea is to let the data tell us what HP to use. For given data, the optimal HP is obtained from the minimum distance between the MLE and MPLE. A bootstrap-based method is also proposed. These methods are compared with existing approaches. The performance evaluation experiments for GEVD by Monte Carlo simulation show that the proposed methods work well for bias and mean squared error. The methods are applied to Blackstone river data and Korean heavy rainfall data to show better performance over MLE, the method of L-moments estimator, and existing MPLEs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.107-115
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• 2020

Support vector regression (SVR) is devised to solve the regression problem by utilizing the excellent predictive power of Support Vector Machine. In particular, the ⲉ-insensitive loss function, which is a loss function often used in SVR, is a function thatdoes not generate penalties if the difference between the actual value and the estimated regression curve is within ⲉ. In most studies, the ⲉ-insensitive loss function is used symmetrically, and it is of interest to determine the value of ⲉ. In SVQR (Support Vector Quantile Regression), the asymmetry of the width of ⲉ and the slope of the penalty was controlled using the parameter p. However, the slope of the penalty is fixed according to the p value that determines the asymmetry of ⲉ. In this study, a new ε-insensitive loss function with p1 and p2 parameters was proposed. A new asymmetric SVR called GSVQR (Generalized Support Vector Quantile Regression) based on the new ε-insensitive loss function can control the asymmetry of the width of ⲉ and the slope of the penalty using the parameters p1 and p2, respectively. Moreover, the figures show that the asymmetry of the width of ⲉ and the slope of the penalty is controlled. Finally, through an experiment on a function, the accuracy of the existing symmetric Soft Margin, asymmetric SVQR, and asymmetric GSVQR was examined, and the characteristics of each were shown through figures.

• Transactions of Materials Processing
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• v.12 no.1
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• pp.34-42
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• 2003

This paper presents a rigid-plastic finite element method to handle the frictional contact problem between two deformable bodies experiencing large deformation. The variational formulation combined with incremental quasi-static model is employed for treating the contact boundary condition. The frictional behavior of the model obeys Coulomb's law of friction. The proposed contact algorithms are classified into two categories, one for searching contacting nodes and the other for calculating contact forces at the contact surface. A slave node and master contact segment are defined using the geometric condition of finite elements on the contact interface. The penalty parameter is used to limit the penetration between contacting bodies, and the finite elements are coupled with contact boundary elements.us gates and cavity thicknesses. Through this study we have observed that the jetting is related to the die swell of material. This means that the jotting is strongly affected by the elastic flow property rather than the viscous flow property in viscoelastic characteristics of molten polymer. Different resins have different elastic properties, and elastic flow behavior depends on the shear rate of flow, i.e. injection speed. Large die swell would eliminate jetting however, the retardation of die swell would stimulate jetting. In the point of mole design, reducing the thickness ratio of cavity to gate can reduce or eliminate jetting regardless of amount of elasticity of polymer melt.