• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.775-778
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• 2000

2채널의 MPEG-2 Layer-Ⅲ 오디오 복호화 알고리듬이 16비트의 고정소수점 연산기로도 고음질의 오디오출력을 얻을 수 있도록 최적화를 수행하였다. 고음질을 얻기 위하여 고정소수점 연산기에서 발생하는 양자화 오차를 최소화 하였으며 각 복호화 과정 별로 최소의 오차를 발생시키는 알고리듬을 제안하고 사용하였다. 고정소수점 모의실험은 C-언어를 사용하여 수행되었으며, ISO-IEC 13818-4 Compliance Test를 수행하여 최적화된 복호화기가 ISO／IEC 13818-4 audio decoder의 기준을 만족함을 보였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.165-168
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• 2001

본 논문은 비선형 헬리콥터 시스템의 퍼지 비례-적분-미분 (PID) 제어기의 설계기법을 제안한다. 퍼지 제어기는 풍부한 자유도를 포함하므로 비선형 시스템의 제어에 매우 적합하다. 그러나 이의 설계는 전문가의 지식에 의존하므로 시스템의 정확한 지식의 획득에 어려울 경우 우수한 성능을 보장하는 제어기의 설계가 매우 어렵다. 따라서 본 논문에서는 제안된 퍼지 PID 제어기의 성능 향상 및 최적화를 위하여 전역적 비선형 최적화 기법인 유전 알고리듬 (GA)을 도입한다. 본 논문에서 제안한 퍼지 PID 제어기의 설계기법은 실제 비선형 헬리콥터 실험 장치에 적용하여 그 효용성 및 실제 산업분야에의 응용 가능성을 보인다.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.420-424
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• 2003

Stacking sequence optimization needs discrete programming techniques because ply angles are limited to a fixed set of angles such as $0^{\circ},\;{\pm}45^{\circ},\;90^{\circ}$. Two typical methods are genetic algorithm and branch and bound method. The goal of this paper is to compare the methods in the light of their efficiency and performance in handling the constraints and finding the global optimum. For numerical examples, maximization of buckling load is used as objective and optimization results from each method are compared.

• Korean Management Science Review
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• v.18 no.2
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• pp.117-124
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• 2001

This paper presents a machining parameter selection approach using an evolutionary computation (EC). In order to perform a successful material cutting process, the engineer is to select suitable machining parameters. Until now, it has been mostly done by the handbook look-up or solving optimization equations which is inconvenient when not in handy. The main thrust of the paper is to provide a handy machining parameter selection approach. The EC is applied to rapidly find optimal machining parameters for the user\\`s specific machining conditions. The EC is basically a combination of genetic a1gorithm and microcanonical stochastic simulated annealing method. The approach is described in detail with an application example. The paper concludes with a discussion on the potential of the proposed approach.

• Computational Structural Engineering
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• v.17 no.2
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• pp.24-30
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• 2004

21세기에 들어서면서 구조설계최적화 알고리듬이 성숙 단계에 이르렀다. 이 단계에 도달하기까지 설계최적화와 관련한 매우 다양한 개념이 소개되었으며 이러한 개념은 구조물의 성능을 향상시키기 위한 컴퓨터 시뮬레이션 도구의 개발로 이어지고 있다. (중략)

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.251-254
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• 2002

In the design of mobile wireless communication system, the location of BTS(Base Transciver Stations), RSC(Base Station Controllers), and MSC(Mobile Switching Center) is one of the most important parameters. Designing wireless communication system, the cost of equipment is need to be made low by combining various, complex parameters. We can solve this problem by combinatorial optimization algorithm, such as Simulated Annealing, Tabu Search, Genetic Algorithm, Random Walk Algorithm that have been extensively used for global optimization. This paper shows the four kind of algorithms which are applied to the location optimization of BTS, BSC, and MSC in designing mobile communication system and then we compare with these algorithms. And also we analyze the experimental results and shows the optimization process of these algorithms. As a the channel of a CDMA system is shared among several users, the receivers face the problem of multiple-access interference (MAI). Also, the multipath scenario leads to intersymbol interference (ISI). Both components are undesired, but unlike the additive noise process, which is usually completely unpredictable, their space-time structure helps to estimate and remove them.

• Journal of the Korea Institute of Building Construction
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• v.17 no.4
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• pp.369-375
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• 2017

This study suggests PSO(Particle Swarm Optimization) algorithm that optimizes the snowplow route allocation and the location of the snow control material storage to improve the efficiency in snow removal works. The modified PSO algorithm for improving the search capacity is proposed, and this study suggests the solution representation, the parameter setting, and the fitness function for the given optimization problems. Computational experiments in real-world case are carried out to justify the proposed method and compared with the traditional PSO algorithms. The results show that the proposed algorithms can find the better solution than the traditional PSO algorithms by searching for the wider solution space without falling into the local optima. The finding of this study is efficiently employed to solve the optimization of the snowplow route allocation by minimizing the workload of each snowplow to search the location of the snow control material storage as well.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.9
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• pp.29-37
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• 1998

In weighted random pattern testing it is an important issue to find the optimal weight sets for achieving a high fault coverage using a small number of weighted random patterns. In this paper, a new weight set optimization algorithm is developed, which can generate the optimal weight sets in an efficient way using the sampling probabilities of deterministic tests patterns. In addition, the simulation based method of finding the proper maximum Hamming distance is presented. Experimental results for ISCAS 85 benchmark circuits prove the effectiveness of the new weight set optimization algorithm and the method of finding the proper maximum Hamming distance.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.8
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• pp.1149-1154
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• 2013

In this paper, an algorithm having new edge growth with depth constraints for constructing Tanner graph of LDPC(Low density parity check) codes is proposed. This algorithm reduces effectively the number of small stoping set in the graph and has lower complexity than other algorithm. The simulation results shows the improved performance of the LDPC codes constructed by this algorithm.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.164-170
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• 2006

This paper proposes a RSM-based hybrid evolutionary algorithm (RHEA) which combines the merits of the popular programs such as genetic algorithm (GA), tabu search method, response surface methodology (RSM). This algorithm, for improving the convergent speed that is thought to be the demerit of genetic algorithm, uses response surface methodology and simplex method. The mutation of GA offers random variety to finding the optimum solution. In this study, however, systematic variety can be secured through the use of tabu list. Efficiency of this method has been proven by applying traditional test functions and comparing the results to GA. And it was also proved that the newly suggested algorithm is very effective to find the global optimum solution to minimize the weight for avoiding the resonance of fresh water tank that is placed in the rear of ship. According to the study, GA's convergent speed in initial stages is improved by using RSM method. An optimized solution is calculated without the evaluation of additional actual objective function. In a summary, it is concluded that RHEA is a very powerful global optimization algorithm from the view point of convergent speed and global search ability.