• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.229-235
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• 2020

Investors aim to maximize the return rate for their own investment, utilizing various information as possible as they can access. However those investors, especially individual investors, have limitations of interpretation of the domain-specific information or even the acquisition of the information itself. Thus, individual investors tend to make decision affectively and frequently, which may cause a loss in returns. This study aims to analyze analysts' target price and to suggest the strategy that could maximize individual's return rate. Most previous literature revealed that the optimistic bias exists in the analysts' target price and it is also confirmed in this study. In this context, this study suggests the upper limit of target rate of returns and the optimal value named 'alpha(α)' which performs the adjustment of proposed target rate to maximize excess earning returns eventually. To achieve this goal, this study developed an optimization problem using linear programming. Specifically, when the analysts' proposed target rate exceeds 30%, it could be adjusted to the extent of 59% of its own target rate. As apply this strategy, the investors could achieve 1.2% of excess earning rate on average. The result of this study has significance in that the individual investors could utilize analysts' target price practically.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1246-1250
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• 2011

This paper considers the container storage problem determining storage position of inbound containers in a container yard at a rail freight terminal. The objective of the problem is to minimize the total number of rehandles when storing/retrieving containers onto/from stacks in the yard. Rehandle implies the temporary removal from and placement back onto the stack to retrieval a target container. In order to solve the problem, we formulate the problem as a binary integer program.

• Journal of applied mathematics & informatics
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• v.7 no.1
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• pp.125-137
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• 2000

A solution of the findpath problem in which a moving object in required to avoid moving obstacles and move to the designated target in the plane is porcided via the second method of Lyapunov. This paper presents an new control designed by a family of piecewise Lyapunov functions to solve a findpath problem and gives some simultion results of that.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.131-136
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• 2003

The problem of maneuvering target tracking has been studied in the field of the state estimation over decades. The Kalman filter has been widely used to estimate the states of the target, but in the presence of a maneuver, its performance may be seriously degraded. In this paper, to solve this problem and track a maneuvering target effectively, DNA coding-based intelligent Kalman filter (DNA coding-based IKF) is proposed. The proposed method can overcome the mathematical limits of conventional methods and can effectively track a maneuvering target with only one filter by using the fuzzy logic based on DNA coding method. The tracking performance of the proposed method is compared with those of the adaptive interacting multiple model (AIMM) method and the GA-based IKF in computer simulations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.108-116
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• 2015

A missile defense system is composed of radars detecting incoming missiles aiming at defense assets, command control units making the decisions on weapon target assignment, and artillery batteries firing of defensive weapons to the incoming missiles. Although, the technology behind the development of radars and weapons is very important, effective assignment of the weapons against missile threats is much more crucial. When incoming missile targets toward valuable assets in the defense area are detected, the asset-based weapon target assignment model addresses the issue of weapon assignment to these missiles so as to maximize the total value of surviving assets threatened by them. In this paper, we present a model for an asset-based weapon assignment problem with shoot-look-shoot engagement policy and fixed set-up time between each anti-missile launch from each defense unit. Then, we show detailed linear approximation process for nonlinear portions of the model and propose final linear approximation model. After that, the proposed model is applied to several ballistic missile defense scenarios. In each defense scenario, the number of incoming missiles, the speed and the position of each missile, the number of defense artillery battery, the number of anti-missile in each artillery battery, single shot kill probability of each weapon to each target, value of assets, the air defense coverage are given. After running lpSolveAPI package of R language with the given data in each scenario in a personal computer, we summarize its weapon target assignment results specified with launch order time for each artillery battery. We also show computer processing time to get the result for each scenario.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.4
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• pp.320-328
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• 2003

This paper proposes a new nonlinear adaptive guidance law. Fourth order state equation for integrated guidance and control loop is formulated considering target uncertainties and control loop dynamics. The state equation is further changed into the normal form by nonlinear coordinate transformation. An adaptive nonlinear guidance law is proposed to compensate for the uncertainties In both target acceleration and control loop dynamics. The proposed law adopts the sliding mode control approach with adaptation fer unknown bound of uncertainties. The present approach can effectively solve the existing guidance problem of target maneuver and the limited performance of control loop. We provide the stability analyses and demonstrate the effectiveness of our scheme through simulations.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.479-482
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• 2004

In this article we consider a single maneuvering target Tracking algorithm in the presence of missing measurements and high clutter environments for multi-sensor target tracking problem. The tracking algorithm is based on the Particle filtering method to predict and update target states. Proposed is the AMM-PF(Auxiliary Multiple Model Particle Filter)[2] method for maneuvering target tracking to improve performance in track estimate and maintenance with a high level of uncertainty. The algorithm we propose is compared to the Extended Kalman Filter(EKF). A simulation study is included.

• Journal of the military operations research society of Korea
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• v.17 no.1
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• pp.159-176
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• 1991

The probability of target survival is the most important factor in the target assignment, Most of the studies about it have assumed the case of one target and ane weapon type. Therefore, they can not be applied to the real situation. In this paper. the quantity and type of enemy assets of the friendly force are considered simultaneously. Considered defense type is the coordinated defense with no impact point prediction. The objective function is to minimize the expected total survival value of targets which are scattered in the defense area. The rules of aircraft assignment are as follows : first, classify targets into several groups, each of those has the same desired damage level secondly. select the critical group which has the least survival value in accordance with the additional aircraft assignment, and finally. assign the same number of attack assets against each target in the critical group. In this paper, the attack assets, the escort assets, and the defense assets are considered. The model is useful to not only the simple aircraft assignment problem but also the complicated wargame models.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1500-1504
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• 2005

This paper proposes the design methodology of genetic algorithm (GA)-based fuzzy Kalman filter for tracking the maneuvering target. The performance of the standard Kalman Filter (SKF) has been degraded because mismatches between the modeled target dynamics and the actual target dynamics. To solve this problem, we use the method to estimate the increment of acceleration by a fuzzy system using the relation between maneuver filter residual and non-maneuvering one. To optimize the fuzzy system, a genetic algorithm (GA) is utilized and this is then tuned by the fuzzy logic correction. Finally, the tracking performance of the proposed method has been compared with those of the input estimation (IE) technique and the intelligent input estimation (IIE) through computer simulations.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.4
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• pp.411-421
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• 1992

In the conventional track while scan (TWS) system, there are two major functions to be performed : detection and tracking. These two functions are normally designed and optimised independently. So TWS algorithm ignores the available decision features that can help in resolving the plot-to-track association ambiguity. Therefore conventional TWS system cna't track the targets in a densed multi-target environment. This paper presents a new TWS algorithm for multi-target track to solve the existing TWS system problem in clutter environment. The algorithm proposed in this paper is derived by modifying the part of joint probabilistic data association (JPDA) algotithm to get the one to one correspondence instead of multiple correspondence and combined with maneuvering detection logic so that it could also track the low maneuvering targets. Simulations to confirm the performance are done in crossing, parallel and maneuvering target. The proposed algorithm was successfully tracking targets above target situations.