• International Journal of Aeronautical and Space Sciences
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• v.6 no.2
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• pp.76-83
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• 2005

Thrusters are important actuators where air is rare. Since the maintenance or replacement of thrusters is not easy in such an environment, a thrusting system must be highly reliable. Redundant thrusters are used to meet the reliability requirement. In this paper, a reconfiguration problem for those redundant thrusters is discussed, especially the management or distribution logic of redundant thrusters is focused on. The logic has to be changed if faults occur at thrusters. Reconfiguration is to change the distribution logic to accommodate thrusters' faults. The authors propose a reconfiguration algorithm based on the linear programming method. The authors define the reconfiguration problem as an optimization problem. The performance index is a quantity related with total fuel consumption by thrusters. This algorithm can accommodate multiple faults. Numerical examples are given to show the advantage of the proposed algorithm over existing methods.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.38-43
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• 2022

In this study, there are many difficulties in defining and judging creative people because there is no systematic analysis method using accurate standards or numerical values. Analyze and judge whether In the previous study, A study on the application of rule success cases through machine learning algorithm extraction, a case study was conducted to help verify or confirm the psychological personality test and aptitude test. We proposed a solution to a research problem in psychology using machine learning algorithms, Data Mining's Cross Industry Standard Process for Data Mining, and CRISP-DM, which were used in previous studies. After that, this study proposes a solution that helps to judge creative people by applying the feature selection algorithm. In this study, the accuracy was found by using seven feature selection algorithms, and by selecting the feature group classified by the feature selection algorithms, and the result of deriving the classification result with the highest feature obtained through the support vector machine algorithm was obtained.

• Proceedings of the KIEE Conference
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• 2004.07e
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• pp.92-95
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• 2004

Power transformer is an important apparatus in transforming and delivering the power in a power system. It shows less accident ratio than other system apparatus, but once the accident occurs, it causes long-term operation stoppage and economic loss. It brings high bad spillover effects. Therefore, the role of protective relaying, which is to prevent internal fault a power transformer is highly important. This study proposed advanced algorithm that can clearly determine internal fault of the power transformer and magnetizing inrush, through numerical analysis by using the terminal voltage and input output current.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1106-1108
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• 1997

This paper presents a new approach on genetic algorithms to economic dispatch problem for valve point discontinuities. Proposed approach in this paper on genetic algorithms improves the performance to solve economic dispatch problem for valve point discontinuities through combination in penalty function with death penalty, generation-apart elitism, atavism and heuristic crossover. Numerical results on an actual utility system consisted of 13 thermal units show that the proposed approach is faster and robuster than classical genetic algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.3
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• pp.95-104
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• 2001

In this paper, we consider a maximin version of the linear programming knapsack problem with extended generalized upper bound (GUB) constraints. We solve the problem efficiently by exploiting its special structure without transforming it into a standard linear programming problem. We present an O(n$^3$) algorithm for deriving the optimal solution where n is the total number of problem variables. We illustrate a numerical example.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.41.1-41
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• 2001

Since the advanced control technique such as model predictive control has been introduced to industrial plant, there have been many progresses in the process control. As a way to improve the control performance, the on-line process optimizer was integrated with the advance controller. In this study, a control technique which improves the control. As the number of changes by the optimizer is increased, the control performance of the proposed algorithm is improved. Its control performance is shown via an numerical example.

• Journal of Advanced Navigation Technology
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• v.25 no.5
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• pp.403-408
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• 2021

Harmony Search(HS) algorithm is an emerging meta-heuristic optimization algorithm, which is inspired by the music improvisation process and has been successfully applied to solve different optimization problems. In order to further improve the performance of HS, this paper proposes a new method which is called Fast Harmony Search(FSH) algorithm. For the purpose, this paper suggest a method to unify two independent improvisation processes by newly defining the boundary value of a object variable using HM. As the result, the process time of the algorithm is shorten and explicit decision of bandwidth is no more needed. Furthermore, exploitative power of random selection is improved. The numerical results reveal that the proposed algorithm can find better solutions and is faster when compared to the conventional HS.

• Journal of Aerospace System Engineering
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• v.17 no.2
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• pp.78-85
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• 2023

For Multi-UAV systems, a task allocation could be a key factor to determine the capability to perform a task. In this paper, we proposed a task allocation method based on genetic algorithm for minimizing makespan and satisfying various constraints. To obtain the optimal solution of the task allocation problem, a huge calculation effort is necessary. Therefore, a genetic algorithm-based method could be an alternative to get the answer. Many types of UAVs, tasks, and constraints in real worlds are introduced and considered when tasks are assigned. The proposed method can build the task sequence of each UAV and calculate waiting time before beginning tasks related to constraints. After initial task allocation with a genetic algorithm, waiting time is added to satisfy constraints. Multiple numerical simulation results validated the performance of this mission planning method with minimized makespan.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.53.2-53.2
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• 2011

We combine the physics of the ellipsoidal collapse model with the excursion set theory to study the shapes of dark matter halos. In particular, we develop an analytic approximation to the nonlinear evolution that is more accurate than the Zeldovich approximation; we introduce a planar representation of halo axis ratios, which allows a concise and intuitive description of the dynamics of collapsing regions and allows one to relate the final shape of a halo to its initial shape; we provide simple physical explanations for some empirical fitting formulae obtained from numerical studies. Comparison with simulations is challenging, as there is no agreement about how to define a non-spherical gravitationally bound object. Nevertheless, we find that our model matches the conditional minor-to-intermediate axis ratio distribution rather well, although it disagrees with the numerical results in reproducing the minor-to-major axis ratio distribution. In particular, the mass dependence of the minor-to-major axis distribution appears to be the opposite to what is found in many previous numerical studies, where low-mass halos are preferentially more spherical than high-mass halos. In our model, the high-mass halos are predicted to be more spherical, consistent with results based on a more recent and elaborate halo finding algorithm, and with observations of the mass dependence of the shapes of early-type galaxies. We suggest that some of the disagreement with some previous numerical studies may be alleviated if we consider only isolated halos.

• International Journal of Advanced Culture Technology
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• v.8 no.1
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• pp.62-70
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• 2020

As an effective means of price discrimination, some suppliers offer trade credit to the distributors in order to stimulate the demand for the product they produce. The availability of the delay in payments from the supplier enables discount of the distributor's selling price from a wider range of the price option in anticipation of increased customer's demand. Since the distributor's lot-size is affected by the demand for the customer, the distributor's lot-size and the selling price determination problem is interdependent and must be solved at the same time. Also, in many common business transactions, the distributor pays the shipping cost for the order and hence, the distributor's ordering cost consists of a fixed ordering cost and the shipping cost that depend on the order quantity. In this regard, we deal with the joint lot-size and price determination problem when the supplier allows delay in payments for an order of a product. The positive effects of credit transactions can be integrated into the EOQ (economic order quantity) model through the consideration of retailing situations, where the customer's demand is a function of the distributor's selling price. It is also assumed that the distributor's order cost consists of a fixed ordering cost and the variable shipping cost. We formulate the distributor's mathematical model from which the solution algorithm is derived based on properties of an optimal solution. A numerical example is presented to illustrate the algorithm developed.