• 대한전자공학회논문지TC
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• 제38권11호
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• pp.30-40
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• 2001

본 논문은 무선 ATM 망에서 VBR 서비스의 가변적인 슬롯 요구량을 신속하고 정확하게 반영함으로써 무선 구간에서의 전송 효율을 최대화할 수 있는 Hybrid DP 제어기법 기반의 동적 슬롯 할당 알고리즘을 제안한다. 제안한 Hybrid DP 제어기법은 기존의 In-band 제어기법과 Out-of-band 제어기법의 장점을 보존하고 단점 및 제어의 한계성을 개선한 방법으로 이동 단말기의 버퍼 상태 변화에 따라 기지국으로 전송되는 ATM 셀에 동적 파라미터 값을 삽입하거나 별도의 제어 채널을 사용하여 단말기의 필요 슬롯 수를 기지국에 전송하는 방식이다. 따라서 VBR 서비스의 유동적인 데이터 발생률을 효율적으로 기지국에게 전송하여 슬롯 할당에 반영함으로써 제한된 무선 채널을 효율적으로 이용하면서 VBR 서비스의 QoS를 보장할 수 있다. 제안한 동적 슬롯 할당 알고리즘의 성능 평가를 위해 해석적 분석 및 시뮬레이션을 실시하였으며, 할당효율, 지연 및 셀 손실률 관점에서 기존의 제어기법보다 우수한 성능을 보였다.

• 한국통신학회논문지
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• 제33권10A호
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• pp.987-996
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• 2008

본 논문에서는 기존 리더 충돌방지 알고리즘인 Channel Monitoring 알고리즘, Pulse Protocol 알고리즘에 대하여 살펴보고, 태그인식시간을 감소시키고, 데이터 처리량, 시스템 효율을 증가 시킬 수 있는 슬롯 점유확률을 이용한 Pulse Protocol 기반의 Hybrid 리더 충돌 방지 알고리즘을 제안한다. 제안하는 알고리즘은 Pulse Protocol 알고리즘의 성능을 향상시키기 위하여 Channel Monitoring 알고리즘에서 사용되고 있는 슬롯의 점유확률 (Occupied Probability)을 이용한다. 즉, 리더들은 랜덤 backoff 시간을 생성한 후, 자신이 사용하게 될 슬롯의 점유확률을 확인하고, 이 슬롯의 점유확률이 0보다 크다면, 새로운 랜덤 backoff 시간을 생성하여 리더간의 충돌을 피한다. 기존 알고리즘들과 제안하는 알고리즘과의 성능을 태그인식시간, 데이터 처리량 및 시스템 효율 등의 성능분석항목들을 통하여 비교 및 분석하여, 제안하는 알고리즘에 의하여 리더의 개수가 증가함에 따라 7% 정도의 태그인식시간 및 데이터 처리량 성능 향상을 확인한다.

• Journal of Electrical Engineering and Technology
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• 제6권2호
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• pp.202-207
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• 2011

Numerous methodologies have been developed in an effort to reduce cogging torque. However, most of these methodologies have side effects that limit their applications. One approach is the optimization methodology that determines an optimized design variable within confined conditions. The response surface methodology (RSM) and the genetic algorithm (GA) are powerful instruments for such optimizations and are matters of common interest. However, they have some weaknesses. Generally, the RSM cannot accurately describe an object function, whereas the GA is time consuming. The current paper describes a novel GA and RSM hybrid algorithm that overcomes these limitations. The validity of the proposed algorithm was verified by three test functions. Its application was performed on a surface-mounted permanent magnet.

• Structural Engineering and Mechanics
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• 제46권3호
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• pp.403-416
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• 2013

This paper describes new optimization strategy that offers significant improvements in performance over existing methods for geometry design of frame structures. In this study, an imperialist competitive algorithm (ICA) and ant colony optimization (ACO) are combined to reach to an efficient algorithm, called Imperialist Competitive Ant Colony Optimization (ICACO). The ICACO applies the ICA for global optimization and the ACO for local search. The results of optimal geometry for three benchmark examples of frame structures, demonstrate the effectiveness and robustness of the new method presented in this work. The results indicate that the new technique has a powerful search strategies due to the modifications made in search module of ICACO. Higher rate of convergence is the superiority of the presented algorithm in comparison with the conventional mathematical methods and non hybrid heuristic methods such as ICA and particle swarm optimization (PSO).

• 산업공학
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• 제8권1호
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• pp.23-30
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• 1995

Optimization in the engineering design is to select the best of many possible design alternatives in a complex design space. One major problem of local minimization algorithm is that they often result in local optima. In this paper, a hybrid method was developed by coupling the genetic algorithm and a traditional direct search method. The proposed method first finds a region for possible global optimum using the genetic algorithm and then searchs for a global optimum using the direct search method. To evaluate the performance of the hybrid method, it was applied to three test problems and a problem of designing corrugate bulkhead of a ship.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권3호
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• pp.259-265
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• 2004

In this study, a hybrid genetic algorithm merged with simulated annealing is presented to solve nonlinear channel blind equalization problems. The equalization of nonlinear channels is more complicated one, but it is of more practical use in real world environments. The proposed hybrid genetic algorithm with simulated annealing is used to estimate the output states of nonlinear channel, based on the Bayesian likelihood fitness function, instead of the channel parameters. By using the desired channel states derived from these estimated output states of the nonlinear channel, the Bayesian equalizer is implemented to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with those of a conventional genetic algorithm(GA) and a simplex GA. In particular, we observe a relatively high accuracy and fast convergence of the method.

• 전기학회논문지
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• 제57권8호
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• pp.1334-1341
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• 2008

This paper introduces an approach of Hybrid Particle Swarm Optimization(HPSO) for a security-constrained economic dispatch(SCED) with line flow constraints. To reduce a early convergence effect of PSO algorithm, we proposed HPSO algorithm considering a mutation characteristic of Genetic Algorithm(GA). In power system, for considering N-1 line contingency, we have chosen critical line contingency through a process of Screening and Selection based on PI(performance Index). To prove the ability of the proposed HPSO in solving nonlinear optimization problems, SCED problems with nonconvex solution spaces are considered and solved with three different approach(Conventional GA, PSO, HPSO). We have applied to IEEE 118 bus system for verifying a usefulness of the proposed algorithm.

• 산업경영시스템학회지
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• 제33권2호
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• pp.48-55
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• 2010

Reliability has been considered as a one of the major design measures in various industrial and military systems. The main objective is to suggest a mathematical programming model and a hybrid parallel genetic algorithm(HPGA) for the problem that determines the optimal component reliability to maximize the system reliability under cost constraint in this study. Reliability optimization problem has been known as a NP-hard problem and normally formulated as a mixed binary integer programming model. Component structure, reliability, and cost were computed by using HPGA and compared with the results of existing meta-heuristic such as Ant Colony Optimization(ACO), Simulated Annealing(SA), Tabu Search(TS) and Reoptimization Procedure. The global optimal solutions of each problem are obtained by using CPLEX 11.1. The results of suggested algorithm give the same or better solutions than existing algorithms, because the suggested algorithm could paratactically evolved by operating several sub-populations and improving solution through swap and 2-opt processes.

• 한국항공우주학회지
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• 제46권7호
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• pp.602-609
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• 2018

본 논문은 LTE 통신망 환경에서 군집 UAV의 비디오 영상 데이터를 고속으로 암호화하기 위한 하이브리드 암호시스템을 제안한다. 이 암호시스템은 ECC 공개키 알고리즘과 LEA 대칭키 알고리즘으로 구성된다. ECC는 RSA보다 빠르면서 동일한 보안성을 가지며, LEA는 동일한 키로 AES보다 빠른 국내 표준 알고리즘이다. 본 논문은 OpenSSL과 OpenCV를 활용하여 Socket 프로그램으로 8개의 군집 UAV 환경에서 하이브리드 암호시스템을 구성하여 구현하였다. 실험을 통하여 본 하이브리드 암호시스템이 실시간 환경에서 효율적으로 적용이 가능함을 보인다.

• International Journal of Control, Automation, and Systems
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• 제1권3호
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• pp.289-300
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• 2003

In this paper, we introduce an identification method in Fuzzy Relation-based Fuzzy Neural Networks (FRFNN) through a hybrid identification algorithm. The proposed FRFNN modeling implement system structure and parameter identification in the efficient form of "If...., then... " statements, and exploit the theory of system optimization and fuzzy rules. The FRFNN modeling and identification environment realizes parameter identification through a synergistic usage of genetic optimization and complex search method. The hybrid identification algorithm is carried out by combining both genetic optimization and the improved complex method in order to guarantee both global optimization and local convergence. An aggregate objective function with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. The proposed model is experimented with using two nonlinear data. The obtained experimental results reveal that the proposed networks exhibit high accuracy and generalization capabilities in comparison to other models.er models.