• Communications for Statistical Applications and Methods
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• v.22 no.1
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• pp.55-67
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• 2015

An important problem in cluster analysis is the selection of variables that define cluster structure that also eliminate noisy variables that mask cluster structure; in addition, outlier detection is a fundamental task for cluster analysis. Here we provide an automated K-means clustering process combined with variable selection and outlier identification. The Automated K-means clustering procedure consists of three processes: (i) automatically calculating the cluster number and initial cluster center whenever a new variable is added, (ii) identifying outliers for each cluster depending on used variables, (iii) selecting variables defining cluster structure in a forward manner. To select variables, we applied VS-KM (variable-selection heuristic for K-means clustering) procedure (Brusco and Cradit, 2001). To identify outliers, we used a hybrid approach combining a clustering based approach and distance based approach. Simulation results indicate that the proposed automated K-means clustering procedure is effective to select variables and identify outliers. The implemented R program can be obtained at http://www.knou.ac.kr/~sskim/SVOKmeans.r.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.2
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• pp.112-119
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• 2003

Generally, PID controller is not suitable to control multi variable system because it is very difficult to tune the PID gains. However, this paper shows that it is not hard to tune the PID gains if we can find a Jacobian matrix of the system. The Jacobian matrix expresses the ratio of output variations according to input variations. It is possible to adjust the input values in order to reduce the output error using the Jacobian. When the colt function is composed of error related terms, the gradient approach can tune the PID gains to minimize the function. In simulation, a hydrofoil catamaran with two inputs and two outputs is applied as a multi variable system. We can easily get the multi variable PID controller by the proposed teaming method. When the controller is compared with LQR controller, the performance is as good as that of LQR controller with a modeling equation.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.195-205
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• 2005

In decision tree analysis, C4.5 and CART algorithm have some problems of computational complexity and bias on variable selection. But QUEST algorithm solves these problems by dividing the step of variable selection and split point selection. When input variables are continuous, QUEST algorithm uses ANOVA F-test under the assumption of normality and homogeneity of variances. In this paper, we investigate the influence of violation of normality assumption and effect of the transformation of variables in the QUEST algorithm. In the simulation study, we obtained the empirical powers of variable selection and the empirical bias of variable selection after transformation of variables having various type of underlying distributions.

• Journal of the Korean Data and Information Science Society
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• v.23 no.1
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• pp.199-207
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• 2012

Recently, variable selection methods using penalized likelihood with a shrink penalty function have been widely studied in various statistical models including generalized linear models and survival models. In particular, they select important variables and estimate coefficients of covariates simultaneously. In this paper, we develop a penalize h-likelihood method for variable selection in gamma frailty models. For this we use the smoothly clipped absolute deviation (SCAD) penalty function, which satisfies a good property in variable selection. The proposed method is illustrated using simulation study and a practical data set.

• Journal of Families and Better Life
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• v.19 no.6
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• pp.145-155
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• 2001

The purposes of this study were first to construct statistical and econometric models based on Amemiya\`s Type I Tobit mainly addressing the issue of statistical efficiency; second to explore income, price, and curvilinear age effects on the explained variable in order to illustrates its statistical marginal effects related to econometric issues; finally to provide invaluable insight for graphical simulations as a new interpretation approach using Tobit analysis. Results indicated that interpretation for the mean marginal effects of three possible cases of dependent variable was more likely to be evident to understand Tobit results compared to conventional analysis only using latent variable, beta. Results also revealed that prediction value of dependent variable can be possibly and easily projected by the independent variable changed whereas only beta value can not illustrate its projection as independent variables'changes.

• Journal of Power Electronics
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• v.13 no.6
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• pp.1024-1031
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• 2013

This paper addresses linear quadratic regulation (LQR) for variable speed variable pitch wind turbines. Because of the inherent nonlinearity of wind turbines, a set of operating conditions is identified and then a LQR controller is designed for each of the operating points. The feedback controller gains are then interpolated linearly to get a control law for the entire operating region. In addition, the aerodynamic torque and effective wind speed are estimated online to get the gain-scheduling variable for implementing the controller. The potential of this method is verified through simulation with the help of MATLAB/Simulink and GH Bladed. The performance and mechanical load when using LQR are also compared with those obtained when using a PI controller.

• The Journal of Korea Robotics Society
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• v.14 no.4
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• pp.326-332
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• 2019

In the case of conventional soft robots, the basic stiffness is small due to the use of flexible materials. Therefore, there is a limitation that the load that can bear is limited. In order to overcome these limitations, a study on a variable stiffness method has been conducted. And it can be seen that the jamming mechanism is most effective in increasing the stiffness of the soft robot. However, the jamming mechanism as a method in which a large number of variable act together is not even theoretically analyzed, and there is no study on intrinsic principle. In this paper, a study was carried out to increase the stability of the force chain to increase the stiffness due to the jamming transition phenomenon. Particle size variables, backbone mechanisms were used to analyze the stability of the force chains. We choose a jamming mechanism as a variable stiffness method of a soft robot, and improve the effect of stiffness based on theoretical analysis, modeling FEM simulation, prototyping and experiment.

• Communications for Statistical Applications and Methods
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• v.29 no.6
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• pp.629-640
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• 2022

Variable selection is one of the most crucial tasks in supervised learning, such as regression and classification. The best subset selection is straightforward and optimal but not practically applicable unless the number of predictors is small. In this article, we propose directly solving the best subset selection via the genetic algorithm (GA), a popular stochastic optimization algorithm based on the principle of Darwinian evolution. To further improve the variable selection performance, we propose to run multiple GA to solve the best subset selection and then synthesize the results, which we call ensemble GA (EGA). The EGA significantly improves variable selection performance. In addition, the proposed method is essentially the best subset selection and hence applicable to a variety of models with different selection criteria. We compare the proposed EGA to existing variable selection methods under various models, including linear regression, Poisson regression, and Cox regression for survival data. Both simulation and real data analysis demonstrate the promising performance of the proposed method.

• Journal of Energy Engineering
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• v.12 no.4
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• pp.309-319
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• 2003

The main purpose of this paper is to present a simulation model for assessing the impacts of a variable speed wind turbine (VSWT) on the distribution network and perform a simulation analysis of volt-age profiles and harmonics along the wind turbine installed feeder using the presented model. The modeled wind energy conversion system consists of a fixed pitch wind turbine and a permanent-magnet synchronous generator, in which a controllable power electronics inverter performs variable speed operation and reactive power output control. Impact analysis on voltage profiles and harmonics of a VSWT-installed distribution feeder is addressed and simulated in terms of steady state and dynamic behaviors. Various capacities and different modes of variable speed wind turbines are simulated and investigated. Case studies demonstrate how feeder voltages are influenced by capacity and control modes of wind turbines and changes in wind speed under various network conditions, and show harmonic impacts on the feeder. Modeling and simulation analysis is based on PSCAD/EMTDC a software package.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.346-351
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• 1987

In this study, digital simulation with nonlinear modeling is carried out to analyse the performance of a hydraulic servomotor system developed for the position control of a large inertia. Nonlinear element, such as nonlinear pressure flow relationships of servovalve, valve spool limits, nonlinear friction, and backlash and resilience of gear system are included in the simulation along with the dynamic characteristics of variable delivery pump compensation mechanism. Simulation results are compared with experimental results for both step and sinusoidal inputs. Independent of input magnitude, both results are in good agreement with minor differences in detail.