• Communications of the Korean Mathematical Society
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• v.30 no.3
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• pp.327-337
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• 2015

This paper is concerned with the optimality conditions for optimal control problem of Belousov-Zhabotinskii reaction model. That is, we obtain the optimality conditions by showing the differentiability of the solution with respect to the control. We also show the uniqueness of the optimal control.

• Communications for Statistical Applications and Methods
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• v.26 no.6
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• pp.527-538
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• 2019

This paper considers the issue of obtaining the optimal design in Poisson regression model when the sample size is small. Poisson regression model is widely used for the analysis of count data. Asymptotic theory provides the basis for making inference on the parameters in this model. However, for small size experiments, asymptotic approximations, such as unbiasedness, may not be valid. Therefore, first, we employ the second order expansion of the bias of the maximum likelihood estimator (MLE) and derive the mean square error (MSE) of MLE to measure the quality of an estimator. We then define DM-optimality criterion, which is based on a function of the MSE. This criterion is applied to obtain locally optimal designs for small size experiments. The effect of sample size on the obtained designs are shown. We also obtain locally DM-optimal designs for some special cases of the model.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.4
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• pp.83-97
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• 2001

Net Present Value (NPV) criterion has been the most widely used criterion to evaluate investment opportunities. However, the analysis based on the NPV criterion falls to consider the managerial flexibility of deferring decisions until major uncertainty is resolved. Recently, real options method attracted a lot of attention as a Powerful approach to address the problem. If investment decision is deferred, the value of the investment opportunity increases but opportunity cost increases at the same time. Therefore, it is important to decide the optimal timing how long the decision can be deferred. In this paper, we developed a model deciding the optimal decision timing. Using the real options approach, the model derived the optimal deferring time until a decision is made. Then, the model was applied to a Korean mobile telecommunications company who wants to invest on the wireless resale business. We believe that this model would be very useful to overcome the problem of NPV decision criterion. With this approach, we can make contingent decisions based on the observation of uncertainly resolutions.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.213-216
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• 2005

In this research, we explore how to manage the transition of technology generations considering incremental innovation of the existing technology generation. Firms can slow down decaying of the existing technology by continuous incremental improvements rather than introducing a new generation technology at the first time if the former strategy is better. We characterize optimal technology transition problem by setting up an optimal control model. The model which is originally designed and solved by Thompson(1968) as a ‘Machine maintenance problem’ has been cited to build the main body of our model. With this analytical model, we derive optimal ‘incremental innovation’ strategy which is considering transition to the next technology. Our analysis indicates that there exists an unique ‘stopping incremental innovation timing’. Before the point of time, the decision maker should make his effort at a maximum level to enhance the current technology. However from the stopping timing to the final time horizon where the new technology is introduced, it is found that not to invest to the current technology any more is optimal.

• Journal of the Korean Society for Library and Information Science
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• v.26
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• pp.167-185
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• 1994

The purpose of this study is to develop the optimal user/librarian interface in information searching. In order to achive the purpose, the 150 unskilled students as subjects have participated in the study. According to the change of the subjects' psychological information states by the access points within the library system, the subjects have been classified into the five types of model: the initial information state, the accepted identification information state, the bibliographic information state, the stack information state, and the location information state. Librarian's searching support is done for 10 minutes at the each access points. To develop the optimal user/librarian interface, the expected values of the models are calculated. The resultants are as follows: 1) The expected value of the initial information states model is 18.94: 2) The expected value of the accepted identification information model is 27.06: 3) The expected value of the bibliographic information state model is 27.06: 4) The expected value of the stack information state model is 22.38: 5) The expected value of the location information state model is 22.38. Those expected values are compared with each other. The model with the lowest expected value is chosen as the optimal user/librarian interface model. In the result, the user's initial information state model of the optimal user/librarian interface in information searching is developed. In order to search the information with the most effect, user must be interfaced with the librarian at his/her own initial information state.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.1
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• pp.1-8
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• 2009

This paper aims mainly to reinterpretate Optimal Bus Scheduling Model by applying System Dynamics Perspective. Traditionally, the study regarding Optimal Bus Scheduling Model stems on the linear relationshp. However, this paper attempted to convert linear relationship based Optimal Bus Scheduling Model to causal loop perspective based Model. In result, the paper present Casual Loop Diagram for Optimal Bus Scheduling Model. Furthermore, the paper also ran a simulation based on Stock & Flow Diagram for Optimal Bus Scheduling Model. The outcome was not much different from the linear relationship based Model due to the similarity of the equation applied on two models.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.137-143
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• 2019

As the performance of computers increases, the use of deep learning, which has faced technical limitations in the past, is becoming more diverse. In many fields, deep learning has contributed to the creation of added value and used on the bases of more data as the application become more divers. The process for obtaining a better performance model will require a longer time than before, and therefore it will be necessary to find an optimal model that shows the best performance more quickly. In the artificial neural network modeling a tuning process that changes various elements of the neural network model is used to improve the model performance. Except Gride Search and Manual Search, which are widely used as tuning methods, most methodologies have been developed focusing on heuristic algorithms. The heuristic algorithm can get the results in a short time, but the results are likely to be the local optimal solution. Obtaining a global optimal solution eliminates the possibility of a local optimal solution. Although the Brute Force Method is commonly used to find the global optimal solution, it is not applicable because of an infinite number of hyper parameter combinations. In this paper, we use a statistical technique to reduce the number of possible cases, so that we can find the global optimal solution.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.73-77
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• 1986

Optimal input design problem for linear regression model with constrained output variance has been considered. It is shown that the optimal input signal for the linear regression model can also be realized as an ARMA process. Monte-Carlo simulation results show that the optimal stochastic input leads to comparatively better estimation accuracy than white input signal.

• East Asian mathematical journal
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• v.35 no.5
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• pp.535-545
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• 2019

This paper is concerned with the optimal control problem associated to strong solution of Belousov-Zhabotinskii reaction model in 2D domain. That is, we otain the global existence of strong solution and show the existence of optimal control.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2001.09a
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• pp.204-207
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• 2001

An optimization process for the design of groundwater remediation is developed by simultaneously considering the well location and the pumping rate. This process uses two independent models: simulation and optimization model. Groundwater flow and contaminant transport are simulated with MODFLOW and MT3D in simulation model. In optimization model, the location and pumping rate of each well are determined and evaluated by the genetic algorithm. In a homogeneous and symmetric domain, the developed model is tested using sequential pairs for pumping rate of each well, and the model gives more improved result than the model using sequential pairs. In application cases, the suggested optimal design shows that the main location of wells is on the centerline of contaminate distribution. The resulting optimal design also shows that the well with maximum pumping rate is replaced with the further one from the contaminant source along flow direction and that the optimal pumping rate declines when more cleanup time is given. But the optimal pumping rate is not linearly proportional to the cleanup time and the minimum total pumping volume does not coincide with the optimal pumping rate.