• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.175-178
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• 2002

A number of controlled selection methods, which have some advantages for practical surveys in considering controls beyond stratification, have developed throughout the last half-century. With respect to the optimization of sampling plan, it is obvious that we may use optimal controlled selection in preference to satisfactory controlled selection. However, there are currently certain restrictions on the employment of optimal controlled selection. We present further research to improve an algorithm for optimal controlled selection and to develop standard software.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.841-843
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• 1997

In this paper we present a Genetic approach to select weighting matrices of LQ(Linear Quadratic) controller for optimal TCSC(Thyristor Controlled Series Capacitor) control. A design of LQ controller depends on choosing weighting matrices. The selection of weighting matrices is usually carried out by trial and error, which is not a trivial problem. We proposed a efficient method using GA of finding weighting matrices for optimal control law. The proposed GA method was applied to design LQ controller of TCSC in one machine infinite bus system and showed good results.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1063-1065
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• 1998

This paper discusses the selection of optimal location of Thyristor Controlled Series Compensator (TCSC) devices to maintain the steady-state voltage profile within limits. A procedure for selecting optimal TCSC location based on sensitivity analysis is developed. This approach identifies the critical lines by evaluating all the voltage magnitudes sensitivity with respect to a line reactance. Computer simulation of a example system is used to verify the proposed procedure.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.14 no.24
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• pp.193-198
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• 1991

Is this paper the selection of a set of process plans is considered for a flexible manufacturing systems. This problem arises in the metal working industry when numerical controlled(N/C) machines are used to manufacture parts. In this paper a new concept to reduce the size of problem is proposed. A corresponding Integer programming model is formulated. The model formulated is to minimize corresponding manufacturing cost and minimize the number of tools and auxiliary devices such as fixtures, grippers, and feeders.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1177-1186
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• 2017

This paper presents a torque ripple reduction method of direct torque control (DTC) using fuzzy controller with optimal selection strategy of voltage vectors in a five-phase induction motor. The conventional DTC method has some drawbacks. First, switching frequency changes according to the hysteresis bands and motor's speed. Second, the torque ripple is rapidly increased in long control period. In order to solve these problems, some/most papers have proposed torque ripple reduction methods by using the optimal duty ratio of the non-zero voltage vector. However, these methods are complicated in accordance with the parameter. If this drawback is eliminated, the torque ripple can be reduced compared with conventional method. In addition, the DTC can be simply controlled without the use of the parameter. Therefore, the proposed algorithm is changing the voltage vector insertion time by using the designed fuzzy controller. Also, the optimized voltage vector selection method is used in accordance with the torque error. Simulation and experimental results show effectiveness of the proposed control algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.450-455
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• 1993

Guidance commands for attitude controlled missiles inevitably take the form of attitude angle commands. On the other hand, many guidance laws compute the accelerations required to achieve their goals. Therefore some integrators must be in use for the attitude controlled missiles to implement the guidance laws. Naturally, the use of the integrator raises the problem of choosing a proper initial value. In this paper, we compute the integrator initial value which minimizes the terminal miss and show that if the total flight time of the mission is long enough, the "optimal" initial value becomes some multiple of the initial heading error or of the given impact angle to the target. We demonstrate the validity of the analysis by showing some linear and nonlinear simulation results.n results.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.672-680
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• 2003

A shopbot is a software agent whose goal is to maximize buyer´s satisfaction through automatically gathering the price and quality information of goods as well as the services from on-line sellers. In the response to shopbots´ activities, sellers on the Internet need the agents called pricebots that can help them maximize their own profits. In this paper we adopts Q-learning, one of the model-free reinforcement learning methods as a price-setting algorithm of pricebots. A Q-learned agent increases profitability and eliminates the cyclic price wars when compared with the agents using the myoptimal (myopically optimal) pricing strategy Q-teaming needs to select a sequence of state-action fairs for the convergence of Q-teaming. When the uniform random method in selecting state-action pairs is used, the number of accesses to the Q-tables to obtain the optimal Q-values is quite large. Therefore, it is not appropriate for universal on-line learning in a real world environment. This phenomenon occurs because the uniform random selection reflects the uncertainty of exploitation for the optimal policy. In this paper, we propose a Mixed Nonstationary Policy (MNP), which consists of both the auxiliary Markov process and the original Markov process. MNP tries to keep balance of exploration and exploitation in reinforcement learning. Our experiment results show that the Q-learning agent using MNP converges to the optimal Q-values about 2.6 time faster than the uniform random selection on the average.

• Journal of applied mathematics & informatics
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• v.30 no.3_4
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• pp.477-488
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• 2012

The convergence rate of a numerical procedure based on Schwarz Alternating Method(SAM) for solving elliptic boundary value problems depends on the selection of the interface conditions applied on the interior boundaries of the overlapping subdomains. It has been observed that the mixed interface condition, controlled by a parameter, can optimize SAM's convergence rate. In [8], one introduced the two-layer multi-parameterized SAM and determined the optimal values of the multi-parameters to produce the best convergence rate for one-dimensional elliptic boundary value problems. In this paper, we present a method which utilizes the one-dimensional result to get the optimal convergence rate for the two-dimensional problem.

• Journal of applied mathematics & informatics
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• v.29 no.1_2
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• pp.161-171
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• 2011

The convergence rate of a numerical procedure based on Schwarz Alternating Method(SAM) for solving elliptic boundary value problems depends on the selection of the interface conditions applied on the interior boundaries of the overlapping subdomains. It has been observed that the Robin condition (mixed interface condition), controlled by a parameter, can optimize SAM's convergence rate. In [7], one had formulated the multi-parameterized SAM and determined the optimal values of the multi-parameters to produce the best convergence rate for one-dimensional elliptic boundary value problems. However it was not successful for two-dimensional problem. In this paper, we present a new method which utilizes the one-dimensional result to get the optimal convergence rate for the two-dimensional problem.

• The Journal of the Acoustical Society of Korea
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• v.18 no.4E
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• pp.43-50
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• 1999

A fast converging coding algorithm that adaptively selects the modes of macroblocks is introduced. For a given frame, the optimal modes are selected based on the decision curves that minimize the overall distortion at a given bit rate. The method proposed in this paper is different from the conventional ones in that it does not manipulate the quantizer to meet the target bit rate but it satisfies the target bit rate by finding optimal modes of macroblocks which result consistent visual quality. Lagrange multiplier of the unconstrained cost function is controlled to trigger decision curves to generate appropriate modes to meet bit rate and the curve is obtained by utilizing simulated annealing optimization technique. The algorithm is implemented within H.261 video codec and simulation results demonstrate superior visual quality.