• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.549-557
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• 2014

Recently, analysis of bargaining game using evolutionary computation is essential issues in field of game theory. In this paper, we observe a bargaining game using co-evolution between two heterogenous artificial agents. In oder to model two artificial agents, we use a particle swarm optimization and a differential evolution. We investigate algorithm parameters for the best performance and observe that which strategy is better in the bargaining game under the co-evolution between two heterogenous artificial agents. Experimental simulation results show that particle swarm optimization outperforms differential evolution in the bargaining game.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.288-297
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• 2003

본 논문은 진화 알고리즘(Evolutionary algorithm)의 기법중의 하나인 유전자 프로그래밍(Genetic programming)을 이용하여 miRNA 유전자를 발굴하기 위한 알고리즘을 소개하고 있다 miRNA는 세포내에서 유전자의 전사를 중지시킴으로써 유전자의 발현을 직접적으로 조절하게 되는 작은 RNA 집단 중의 하나이다. 그러므로 miRNA를 유전체 데이터에서 동정해내는 작업은 생물학적으로 상당히 중요하다. 한편 유전체 데이터에서 miRNA를 동정해내는 알고리즘은 생물학적 실험에서의 시간과 비용을 상당히 절감할 수 있으며, 생물학적으로 miRNA를 동정하는 많은 어려움을 덜어주게 된다. 하지만 계산학적으로 miRNA의 동정은 1차 염기서열상의 통계적인 중요도가 부족하여 기존의 유전자 예측 알고리즘을 적용하기에는 어려움이 있다. 따라서 본 연구에서는 miRNA의 염기서열보다는 2차구조에서 더 많은 유사성을 갖는다는 점을 착안하여, 2차구조내에서 공통적인 구조를 찾아내고, 그 정보를 이용하여 miRNA를 동정해내는 방법으로 접근하였다. 이 알고리즘의 성능평가를 위해 우리는 test set을 이용하여 학습된 모델의 특이도(= 34/38)와 민감도(= 38/67)를 계산하였다. 평가결과 본 알고리즘이 기존의 miRNA 예측 프로그램보다 높은 특이도를 갖고 있으며, 유사한 수준의 민감도를 갖고 있음을 보여 주고 있다.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.3
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• pp.15-23
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• 2013

Weight reduction of a automobile has been steadily tried in automotive industry to improve fuel efficiency, driving performance and the production profits. Since the weight of BIW takes up a large portion of the total weight of the automobile, reducing the weight of BIW greatly contributes to reducing the total weight of the vehicle. To reduce weight, vehicle manufacturers have tried to apply lightweight materials, such as aluminum and high-strength steel, to the components of BIW instead of conventional steel. In this research, material arrangement of an automotive BIW was optimized by formulating a design problem to minimize weight of the BIW while satisfying design requirements about bending and torsional stiffness and perform a metamodel-based design optimization strategy. As a result of the design optimization, weight of the BIW is reduced by 45.7% while satisfying all design requirements.

• Journal of Astronomy and Space Sciences
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• v.31 no.2
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• pp.121-130
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• 2014

Essential ideas, successes, and difficulties of Areal Density Analysis (ADA) for color-magnitude diagrams (CMD's) of resolved stellar populations are examined, with explanation of various algorithms and strategies for optimal performance. A CMD-generation program computes theoretical datasets with simulated observational error and a solution program inverts the problem by the method of Differential Corrections (DC) so as to compute parameter values from observed magnitudes and colors, with standard error estimates and correlation coefficients. ADA promises not only impersonal results, but also significant saving of labor, especially where a given dataset is analyzed with several evolution models. Observational errors and multiple star systems, along with various single star characteristics and phenomena, are modeled directly via the Functional Statistics Algorithm (FSA). Unlike Monte Carlo, FSA is not dependent on a random number generator. Discussions include difficulties and overall requirements, such as need for fast evolutionary computation and realization of goals within machine memory limits. Degradation of results due to influence of pixelization on derivatives, Initial Mass Function (IMF) quantization, IMF steepness, low Areal Densities ($\mathcal{A}$), and large variation in $\mathcal{A}$ are reduced or eliminated through a variety of schemes that are explained sufficiently for general application. The Levenberg-Marquardt and MMS algorithms for improvement of solution convergence are contained within the DC program. An example of convergence, which typically is very good, is shown in tabular form. A number of theoretical and practical solution issues are discussed, as are prospects for further development.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.3
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• pp.246-255
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• 2017

The proposed design methodology represents a new approach to optimize the propeller-hull system simultaneously. In this paper, two objective functions are considered, the first objective function is Lifetime Fuel Consumption (LFC) and the other one is cost function including thrust, torque, open water and skew efficiencies. The variables of the propeller geometries (Z, EAR, P/D and D) and ship hull parameters (L/B, B/T, T and $C_B$) are considered to be optimized with cavitation, blades stress of propeller. The well-known evolutionary algorithm based on NSGA-II is employed to optimize a multi-objective problem, where the main propeller and hull dimensions are considered as design variables. The results are presented for a series 60 ship with B-series propeller. The results showed that the proposed method is an appropriate and effective approach for simultaneously propeller-hull system design and is able to minimize both of the objective functions significantly.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1355-1360
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• 2005

In this paper, we approach the problem of image filter design automation using a kind of intrinsic evolvable hardware architecture. For the purpose of implementing the intrinsic evolution process in a common FPGA chip and evolving a complicated digital circuit system-image filter, the design automation system employs the reconfigurable circuit architecture as the reconfigurable component of the EHW. The reconfigurable circuit architecture is inspired by the Cartesian Genetic Programming and the functional level evolution. To increase the speed of the hardware evolution, the whole evolvable hardware system which consists of evolution algorithm unit, fitness value calculation unit and reconfigurable unit are implemented by a commercial FPGA chip. The Celoxica RC1000 card which is fitted with a Xilinx Virtex xcv2000E FPGA chip is employed as the experiment platform. As the result, we conclude the terms of the synthesis report of the image filter design automation system and hardware evolution speed in the Celoxica RC1000 card. The evolved image filter is also compared with the conventional image filter form the point of filtered image quality.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.610-616
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• 2004

In the research of biomechanical engineering, robotics and neurophysiology, to clarify the mechanism of human bipedal walking is of major interest. It serves as a basis of developing several applications such as rehabilitation tools and humanoid robots. Nevertheless, because of complexity of the neuronal system that interacts with the body dynamics system to make walking movements, much is left unknown about the details of locomotion mechanism. Researchers were looking for the optimal model of the neuronal system by trials and errors. In this paper, we applied Genetic Programming to induce the model of the nervous system automatically and showed its effectiveness by simulating a human bipedal walking with the obtained model.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1036-1041
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• 2006

본 연구에서는 허브와 스포크의 입지선정과 차량 경로가 통합된 hub-and-spoke 네트워크 설계문제를 다룬다. Hub-and-spoke 네트워크는 대량화와 공동화를 통해 물류효율화를 실현하기 위한 대표적인 구조로 물류시스템에서 흔히 사용되고 있다. 이러한 물류시스템에서 물류비용의 절감과 고객서비스 향상을 위한 효율적인 수송네트워크 설계는 매우 중요하다. 전통적인 hub-and-spoke 네트워크 설계문제에서 각 스포크의 위치와 화물량이 미리 주어진 상황에서 허브의 입지를 결정하였다. 하지만 스포크 역시 스포크가 담당하는 고객들의 위치와 담당 영역에 따라 그 위치와 수, 그리고 화물량이 변할 수 있다. 또한 정확한 비용산출을 위해서는 스포크에서 고객으로의 수집과 배달을 위한 차량경로가 함께 고려되어야 한다. 다루는 수송망 설계문제는 상호 관련성 있는 여러 부분문제가 결합된 통합문제로써 이를 해결하는 방법으로 기존의 발견적 방법에 의한 순차적 기법은 한계가 있다. 본 연구에서는 공생 진화알고리듬 기반의 방법론을 채용하여 다루는 수송망 설계문제를 동시에 통합적으로 해결할 수 있는 알고리듬을 개발한다. 실험을 통해 개발한 알고리듬의 우수성과 그 적용성을 보인다.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.273-274
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• 2006

The sea is origin of all lift, and 90% of the all living organisms are in the sea. The biosynthesis is very different. Many organisms are kept on a lower or developed to another evolutionary level than on shore. Our society is increasing demand and need for marine food and this food has to product at onshore or offshore fish farming sites. Ocean fish farms have a special operation properties such as a good quality water, net cage, sheltered locations and feeding system. The farming site is controlled and monitored for fish welfare as ammonia($NH_3$), temperature, the speed of a running fluid. Specially, the fish farm is seriously influenced by ammonia. In this paper, $NH_3$ monitoring system for ocean fish farm is researched for the suitable fish farming sites, and test equipment is designed for achieving practical data. The equipment wit monitoring algorithm is expected to the useful system for ocean fish farm.

• Journal of Electrical Engineering and Technology
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• v.8 no.1
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• pp.53-63
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• 2013

To guide the decision making of the expert engineer specialized in power system operation and control; the practical OPF solution should take in consideration the critical situation due to severe loading conditions and fault in power system. Differential Evolution (DE) is one of the best Evolutionary Algorithms (EA) to solve real valued optimization problems. This paper presents simple Differential Evolution (DE) Optimization algorithm to solving multi objective optimal power flow (OPF) in the power system with shunt FACTS devices considering voltage deviation, power losses, and power flow branch. The proposed approach is examined and tested on the standard IEEE-30Bus power system test with different objective functions at critical situations. In addition, the non smooth cost function due to the effect of valve point has been considered within the second practical network test (13 generating units). The simulation results are compared with those by the other recent techniques. From the different case studies, it is observed that the results demonstrate the potential of the proposed approach and show clearly its effectiveness to solve practical OPF under contingent operation states.