• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.229-232
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• 2001

Recently, several promising multiobjective evolutionary algorithms, e,g, SPEA, NSGA-ll, PESA, and SPEA2, have been developed. In this paper, we also propose a new multiobjective evolutionary algorithm that compares to them. In the algorithm proposed in this paper, we introduce a novel concept, "inherited age" and total algorithm is executed based on the inherited age concept. Also, we propose a new sharing algorithm, called objective classication sharing algorithm(OCSA) that can preserve the diversity of the population. We will show the superior performance of the proposed algorithm by comparing the proposed algorithm with other promising algorithms for the test functions.

• 한국어정보학회:학술대회논문집
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• 2016.10a
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• pp.333-336
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• 2016

본 연구에서는 개체명 인식의 성능을 향상시키기 위해, 가중 투표 방법을 이용하여 개체명 인식 모델을 앙상블 하는 방법을 제안한다. 각 모델은 Conditional Random Fields의 변형 알고리즘을 사용하여 학습하고, 모델들의 가중치는 다목적 함수 최적화 기법인 NSGA-II 알고리즘으로 학습한다. 실험 결과 제안 시스템은 $F_1Score$ 기준으로 87.62%의 성능을 보여, 단독 모델 중 가장 높은 성능을 보인 방법보다 2.15%p 성능이 향상되었다.

• Proceedings of the KIEE Conference
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• 2007.11c
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• pp.179-182
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• 2007

The Design and Optimization of a low-profile antenna for the Satellite Digital Audio Radio System(SDARS) using a Non-Dominated Sorting Genetic Algorithm(NSGA) is presented. a fairly omni-directional elevation gain pattern over 60 degrees < q <60 degrees are obtained. The average value of the LCP gain pattern is approximately 2 dBic. The heights of the antennas are less than 0.251. The cross polarized signal level is approximately 12 dBic less than the co-polarized signal level.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.8
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• pp.689-694
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• 2001

Recently, several promising multiobjective evolutionary algorithm such as SPEA. NSGA-II, PESA, and SPEA2 have been developed. In this paper, we also propose a new multiobjective evolutionary algorithm that compares to them. In the algorithm proposed in this paper, we introduce a novel concept, “inherited age” and total algorithm is executed based on the inherited age concept. Also, we propose a new sharing algorithm, called objective classication sharing algorithm(OCSA) that can preserve the diversity of the population. We will show the superior performance of the proposed algorithm by comparing the proposed algorithm with other promising algorithms for the test functions.

• Annual Conference on Human and Language Technology
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• 2016.10a
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• pp.333-336
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• 2016

본 연구에서는 개체명 인식의 성능을 향상시키기 위해, 가중 투표 방법을 이용하여 개체명 인식 모델을 앙상블 하는 방법을 제안한다. 각 모델은 Conditional Random Fields의 변형 알고리즘을 사용하여 학습하고, 모델들의 가중치는 다목적 함수 최적화 기법인 NSGA-II 알고리즘으로 학습한다. 실험 결과 제안 시스템은 $F_1Score$기준으로 87.62%의 성능을 보여, 단독 모델 중 가장 높은 성능을 보인 방법보다 2.15%p 성능이 향상되었다.

• Journal of the Society of Naval Architects of Korea
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• v.49 no.2
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• pp.174-181
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• 2012

In this paper, the Flow Control Fin(FCF) optimization has been carried out using computational fluid dynamics(CFD) techniques. This study focused on evaluation for the performance of the FCF attached in the stern part of the ship. The main advantage of FCF is to enhance the resistance performance through the lift generation with a forward force component on the foil section, and the propulsive performance by the uniformity of velocity distribution on the propeller plane. This study intended to evaluate these functions and to find optimized FCF form for minimizing viscous resistance and equalizing wake distribution. Four parameters of FCF are used in the study, which were angle and position of FCF, longitudinal location, transverse location, and span length in the optimization process. KRISO 300K VLCC2(KVLCC2) was chosen for an example ship to demonstrate FCF for optimization. The optimization procedure utilized genetic algorithms (GAs), a gradient-based optimizer for the refinement of the solution, and Non-dominated Sorting GA-II(NSGA-II) for Multiobjective Optimization. The results showed that the optimized FCF could enhance the uniformity of wake distribution at the expense of viscous resistance.

• Earthquakes and Structures
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• v.11 no.2
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• pp.347-369
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• 2016

The main objective of this paper is the robust multi-objective optimization design of semi-active tuned mass damper (STMD) system using genetic algorithms and fuzzy logic. For optimal design of this system, it is required that the uncertainties which may exist in the system be taken into account. This consideration is performed through the robust design optimization (RDO) procedure. To evaluate the optimal values of the design parameters, three non-commensurable objective functions namely: normalized values of the maximum displacement, velocity, and acceleration of each story level are considered to minimize simultaneously. For this purpose, a fast and elitist non-dominated sorting genetic algorithm (NSGA-II) approach is used to find a set of Pareto-optimal solutions. The torsional effects due to irregularities of the building and/or unsymmetrical placements of the dampers are taken into account through the 3-D modeling of the building. Finally, the comparison of the results shows that the probabilistic robust STMD system is capable of providing a reduction of about 52%, 42.5%, and 37.24% on the maximum displacement, velocity, and acceleration of the building top story, respectively.

• Journal of Ocean Engineering and Technology
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• v.25 no.4
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• pp.42-47
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• 2011

In this paper, wake equalizing duct (WED) form optimization was carried out using computational fluid dynamics (CFD) techniques. A WED is a ring-shaped flow vane with a foil-type cross-section fitted to a hull in front of the upper propeller area. The main advantage of a WED is the power savings resulting from the uniformity of the velocity distribution on the propeller plane, a reduction in the flow separation at the aft-body, and lift generation with a forward force component on the foil section. This paper intends to evaluate these functions and find an optimized WED form for minimizing the viscous resistance and equalizing the wake distribution. In the optimization process, the study uses four WED parameters: the angle of the section, longitudinal location, and angles of the axes for the half rings against the longitudinal and transverse planes of the ship. KRISO 300K VLCC2 (KVLCC2) is chosen as an example ship to demonstrate the WED optimization. The optimization procedure uses genetic algorithms (GAs), a gradient-based optimizer for the refinement of the solution, and Non-dominated Sorting GA-II(NSGA-II) for Multiobjective Optimization. The results show that the optimized WED can reduce the viscous resistance at the expense of the uniformity of the wake distribution.

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.58.2-58.2
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• 2011

본 연구에서는 5MW급 수평축 풍력터빈 블레이드에 대해 국내 서남해안의 풍속특성을 고려한 최적설계를 수행 하였다. 최적설계를 수행하기 위해 블레이드 해석은 Blade Element and Momentum Theory를 이용 하였으며, 설계 시 적용된 기저형상은 NREL에서 제안한 5MW급 풍력터빈 블레이드을 선정하였다. 최적설계를 수행하기 전 설계에 사용된 설계변수들이 풍속에 대해 어떠한 경향을 가지고 있는지 알아보기 위해 Parametric Study를 수행 하였으며, 최적설계는 다목적 최적화 유전 알고리즘인 NSGA-II를 이용하여 평균풍속이 낮은 서남해안의 연간에너지 생산량과 설비이용률을 최대화하였다. 최적화 결과들로부터 설계 조건에 맞는 최적해를 도출 할 수 있었으며, 이를 통해 기저형상의 연간에너지 생산량 및 설비이용률을 보다 향상 시킬 수 있었다.

• Structural Engineering and Mechanics
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• v.47 no.2
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• pp.227-245
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• 2013

The term "constructability" in regard to cast-in-place concrete construction refers mainly to the ease of reinforcing steel placement. Bar congestion complicates steel placement, hinders concrete placement and as a result leads to improper consolidation of concrete around bars affecting the integrity of the structure. In this paper, a multi-objective approach, based on the non-dominated sorting genetic algorithm (NSGA-II) is developed for optimal design of reinforced concrete cantilever retaining walls, considering minimization of the economic cost and reinforcing bar congestion as the objective functions. The structural model to be optimized involves 35 design variables, which define the geometry, the type of concrete grades, and the reinforcement used. The seismic response of the retaining walls is investigated using the well-known Mononobe-Okabe analysis method to define the dynamic lateral earth pressure. The results obtained from numerical application of the proposed framework demonstrate its capabilities in solving the present multi-objective optimization problem.