• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1653-1660
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• 2016

Smoothly clipped absolute deviation (SCAD) penalty is known to satisfy the desirable properties for penalty functions like as unbiasedness, sparsity and continuity. In this paper, we deal with the regression function estimation and variable selection based on SCAD penalized censored regression model. We use the local linear approximation and the iteratively reweighted least squares algorithm to solve SCAD penalized log likelihood function. The proposed method provides an efficient method for variable selection and regression function estimation. The generalized cross validation function is presented for the model selection. Applications of the proposed method are illustrated through the simulated and a real example.

• Computers and Concrete
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• v.16 no.4
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• pp.587-604
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• 2015

The hybrid-type penalty method (HPM) is suitable for representing failure phenomena occurring during the transition from continua to discontinua in materials such as concrete. Initiation and propagation of dominant cracks and branching of cracks can easily be modeled as a discrete crack. The HPM represents a discrete crack by eliminating the penalty that represents the separation of the elements at the intersection boundary. This treatment is easy because no change in the degrees of freedom for the discrete crack is necessary. In addition, it is important to evaluate the correct deformation of the continua before the crack formation is initiated. To achieve this, we implemented a constitutive model of concrete for the HPM. In this paper, we explain the implemented constitutive model and describe the simulation of an anchor bolt pullout test using the HPM demonstrating its capability for evaluating progressive failure.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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• pp.3-10
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• 1998

Optimization problems may be devided into geometry optimization problems and topology optimization problems. In this paper, a method using tile equivalent material properties prediction techniques of a particulate-reinforced composites is proposed for the topology optimization. This method makes use of penalty factor in order that regions with intermediate value of design variables can be penalized. The computational results being obtained from PLBA algorithm of some values of penalty factor are presented.

• Communications for Statistical Applications and Methods
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• v.22 no.2
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• pp.147-157
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• 2015

We consider a sparse high-dimensional linear regression model. Penalized methods using LASSO or non-convex penalties have been widely used for variable selection and estimation in high-dimensional regression models. In penalized regression, the selection and prediction performances depend on which penalty function is used. For example, it is known that LASSO has a good prediction performance but tends to select more variables than necessary. In this paper, we propose an additive sparse penalty for variable selection using a combination of LASSO and minimax concave penalties (MCP). The proposed penalty is designed for good properties of both LASSO and MCP.We develop an efficient algorithm to compute the proposed estimator by combining a concave convex procedure and coordinate descent algorithm. Numerical studies show that the proposed method has better selection and prediction performances compared to other penalized methods.

• Transactions of Materials Processing
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• v.22 no.3
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• pp.143-149
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• 2013

A new finite element model for the hydrostatic extrusion of a biaxial bar is introduced. In this model, a penalty contact algorithm, which is adopted to replace the traction boundary conditions due to the fluid in the container of the extruder, is incorporated into a consistent penalty finite element formulation for the viscoplastic deformation of a work piece during hydrostatic extrusion. Two parameters, introduced in the penalty contact algorithm in this study, a critical penalty contact pressure $P_0$ and a critical penalty contact distance $D_c$, are carefully examined for various process conditions. The proposed finite element model is applied to the hydrostatic extrusion of a Cu-clad Al bar. The extrusion loads and thickness ratios of the clad materials by the proposed model are compared in detail to values from experiments reported in the literature. Finally, it is concluded that the proposed finite element model is useful in practical implementations.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.450-455
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• 2004

There is few research about contact problem for a rigid surface with an arbitrary shape in SPH. The variational equation based on the virtual work principle is derived and its solution is obtained by the penalty method. It is proposed a new method that can determine the parameters for a penetration and a penetration rate used in the penalty method. The reproducing condition is adopted to correct the deficiency of kernel on the boundary. In order to calculate a penetration of particles, after checking boundary particles for deformable body boundary normal vectors were determined on the rigid surface. Numerical simulations for models which have rigid surface with an arbitrary shape were conducted to validate the proposed method in 2D. The results of those analysis represent that the contact algorithm proposed in this study works properly.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.1 s.232
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• pp.30-37
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• 2005

There is few research about contact problem for a rigid surface with an arbitrary shape in SPH. The variational equation based on the virtual work principle is derived and its solution is obtained by the penalty method. It is proposed a new method that can determine the parameters for a penetration and a penetration rate used in the penalty method. The reproducing condition is adopted to correct the deficiency of kernel on the boundary. In order to calculate a penetration of particles, after checking boundary particles for deformable body, boundary normal vectors were determined on the rigid surface. Numerical simulations for models which have rigid surface with an arbitrary shape were conducted to validate the proposed method in 2D Cartesian and cylindrical coordinate. The results of those analysis represent that the contact algorithm proposed in this study works properly.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.4
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• pp.547-554
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• 2016

Analyze the customer daily load patterns, be used to determine the optimal charging and discharging schedule which can minimize the electrical charges through the battery energy storage system(BESS) installed in consumers is an object of this paper. BESS, which analyzes the load characteristics of customer and reduce the peak load, is essential for optimal charging and discharging scheduling to save electricity charges. This thesis proposes optimal charging and discharging scheduling method, using particle swarm optimization (PSO) and penalty function method, of BESS for reducing energy charge. Since PSO is a global optimization algorithm, best charging and discharging scheduling can be found effectively. In addition, penalty function method was combined with PSO in order to handle many constraint conditions. After analysing the load patterns of target BESS, PSO based on penalty function method was applied to get optimal charging and discharging schedule.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.844-847
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• 1997

In this paper, scheduling problem is dealt for the minimization of due date penalty for the customer order. Multiproduct batch processes have been dealt with for their suitability for high value added low volume products. Their scheduling problems take minimization of process operation for objective function, which is not enough to meet the customer satisfaction and the process efficiency simultaneously because of increasing requirement of fast adaptation for rapid changing market condition. So new target function has been suggested by other researches to meet two goals. Penalty function minimization is one of them. To present more precisely production scheduling, we develop new scheduling model with penalty function of earliness and tardiness We can find many real cases that penalty parameters are divergent by the difference between the completion time of operation and due date. That is to say, the penalty parameter values for the product change by the customer demand condition. If the order charges different value for due date, we can solve it with the due date period. The period means the time scope where penalty parameter value is 0. If we make use of the due date period, the optimal sequence of our model is not always same with that of fixed due date point. And if every product have due date period, due date of them are overlapped which needs optimization for the maximum profit and minimum penalty. Due date period extension can be enlarged to makespan minimization if every product has the same abundant due date period and same penalty parameter. We solve this new scheduling model by simulated annealing method. We also develop the program, which can calculate the optimal sequence and display the Gantt chart showing the unit progress and time allocation only with processing data.

• Journal of the Korean Data and Information Science Society
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• v.22 no.3
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• pp.613-618
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• 2011

The proposed method is based on a penalized log partial likelihood of Cox proportional hazard model with L1-penalty. We use the iteratively reweighted least squares procedure to solve L1 penalized log partial likelihood function of Cox proportional hazard model. It provide the ecient computation including variable selection and leads to the generalized cross validation function for the model selection. Experimental results are then presented to indicate the performance of the proposed procedure.