• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.682-688
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• 2006

This paper deals with the delay-dependent and rate-independent stabilization of systems with multiple unknown time-varying delays and time-varying structured uncertainties. All the linear matrix inequalities based conditions are derived by employing free-weighting matrices to express the relationships between the terms in the Leibniz-Newton formula. The criteria do not require any tuning parameters. Numerical examples demonstrate the validity of the method.

• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.423-432
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• 2012

This paper is concerned with the detection of multiple change-points in linear regression models. The proposed procedure relies on the local estimation for global change-point estimation. We propose a multiple change-point estimator based on the local least squares estimators for the regression coefficients and the split measure when the number of change-points is unknown. Its statistical properties are shown and its performance is assessed by simulations and real data applications.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.165-172
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• 1998

This paper considers a linear regression model with censored data where each error term follows a multivariate normal distribution. In this paper we consider the diffuse prior distribution for parameters of the linear regression model. With censored data we derive the full conditional densities for parameters of a multiple regression model in order to obtain the marginal posterior densities of the relevant parameters through the Gibbs Sampler, which was proposed by Geman and Geman(1984) and utilized by Gelfand and Smith(1990) with statistical viewpoint.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.53-56
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• 2000

The problem ( Ρ ) of optimizing a linear function d$\^$T/x over the set of efficient set for a multiple objective linear program ( Μ ) is difficult because the efficient set is nonconvex. There some interesting properties between the objective linear vector ｄ and the matrix of multiple objectives C and those properties lead us to establish criteria to solve ( Ρ ) with a linear program. In this paper we investigate a system of the linear equations C$\^$T/${\alpha}$=d and construct two linearly independent positive vectors ${\mu}$, ν such that ${\alpha}$=${\mu}$-ν. From those vectors ${\mu}$, ν, solving an weighted sum linear program for finding an efficient extreme point for the ( Μ ) is a way to get an optimal solution ( Ρ ). Therefore our theory gives an easy way of solving nonconvex program ( Ρ ) with a weighted sum linear program.

• Journal of IKEEE
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• v.23 no.1
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• pp.1-8
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• 2019

In this paper, the electrical characteristics with various C-rates are tested with a high power series battery pack comprised of 18650 cylindrical nickel cobalt aluminum(NCA) lithium-ion battery. The electrical characteristics of discharge capacity test with 14S1P battery pack and electric vehicle (EV) cycle test with 4S1P battery pack are compared and analyzed by the various of C-rates. Multiple linear regression is used to estimate voltage imbalance of 14S1P and 4S1P battery packs with various C-rates based on experimental data. The estimation accuracy is evaluated by root mean square error(RMSE) to validate multiple linear regression. The result of this paper is contributed that to use for estimating the voltage imbalance of discharge capacity test with 14S1P battery pack using multiple linear regression better than to use the voltage imbalance of EV cycle with 4S1P battery pack.

• Journal of the Korean Operations Research and Management Science Society
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• v.15 no.2
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• pp.33-44
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• 1990

An efficient algorithm is developed for the linear programming relaxation of generalized multiple choice knaspack problem. The generalized multiple choice knaspack problem is an extension of the multiple choice knaspack problem whose relaxed LP problem has been studied extensively. In the worst case, the computational coimplexity of the proposed algorithm is of order 0(n. $n_{max}$)$^{2}$), where n is the total number of variables and $n_{max}$ denotes the cardinality of the largest multiple choice set. The algorithm can be easily embedded in a branch-and-bound procedure for the generalized multiple choice knapsack problem. A numerical example is presented and computational aspects are discussed.sed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.2
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• pp.314-324
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• 2018

This paper proposes a linear distributed target tracking filter for multiple unmanned aerial vehicles(UAVs) sharing their passive sensor measurements through communication channels. Different from the conventional nonlinear filtering schemes, the distributed passive target tracking problem is newly formulated within the framework of a linear robust state estimation theory incorporated with a linear uncertain measurement equation including the coordinate transform uncertainty. To effectively cope with the performance degradation due to the coordinate transform uncertainty, a linear consistent robust Kalman filter(CRKF) theory is devised and applied for designing a distributed passive target tracking filter. Through the simulations for typical UAV surveillance mission, the superior performance of the proposed method over the existing schemes of distributed passive target tracking are demonstrated.

• Journal of applied mathematics & informatics
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• v.3 no.2
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• pp.129-148
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• 1996

This paper propose the inference mechanism for handling linear polynomial constraints called consistency checking algorithm based on the feasibility checking algorithm borrowed from linear pro-gramming. in contrast with other approaches proposed algorithm can efficiently and coherented by linear polynomial forms. The developed algorithm is successfully applied to the symbolic simulation that offers a convenient means to conduct multiple simultaneous exploration of model behaviors.

• Journal of Korean Institute of Industrial Engineers
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• v.15 no.2
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• pp.23-31
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• 1989

From the supplier's point of view, we examine the existence of a Pareto superior pricing schedule for one wholesaler with multiple retailers. In the case of multiple retailers, an order quantity pricing schedule should depends on the retailer's underlying characteristics. But identification of each retailer's characteristics may be impossible; rather, the wholesaler knows only the probability distribution of each retailer's characteristics. Perfect price discrimination is impossible because a separate pricing schedule cannot be tailored for each retailer. Some degree of discrimination is possible only by using a non-linear pricing schedule. From this analysis based on the non-linear pricing, we conclude that there is no Pareto superior pricing schedule for the case of multiple retailers.

• Environmental Engineering Research
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• v.20 no.3
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• pp.237-245
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• 2015

Particulate matter in indoor environments has caused public concerns in recent years. The objective of this research is to explore the influence of radiators on particle size distributions and concentrations. The particle size distributions as well as concentrations above radiators and in the adjacent indoor air are monitored in forty-two indoor environments in Xi'an, China. The temperatures, relative humidity and air velocities are also measured. The particle size distributions above radiators at ten locations are analyzed. The results show that the functional difference of indoor environments has little impact on the particle size distributions above radiators. Then the effects of the environmental parameters (particle concentrations in the adjacent indoor air, temperatures, relative humidities and air velocities) on particle concentrations above radiators are assessed by applying multiple linear regression analysis. Three multiple linear regression models are established to predict the concentrations of $PM_{10}$, $PM_{2.5}$ and $PM_1$ above radiators.