• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.15-17
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• 2005

Recently genetic algorithm techniques have widely used in adaptive and control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of genetic algorithm constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a genetic algorithm used for identification of the process dynamics of nonlinear IIR filter and it was shown that this method offered superior capability over the genetic algorithm. A genetic algorithm is used to solve the parameter identification problem for linear and nonlinear digital filters. This paper goal estimate nonlinear IIR filter parameter using the genetic algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.502-504
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• 2005

Recently genetic algorithm techniques have widely used in adaptive and control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of genetic algorithm constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a genetic algorithm used for identification of the process dynamics of FIR filter and it was shown that this method offered superior capability over the genetic algorithm. A genetic algorithm is used to solve the parameter identification problem for linear and nonlinear digital filters. This paper goal estimate FIR filter parameter using the genetic algorithm.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 추계학술대회논문집A
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• pp.533-538
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• 2001

This paper describes a combinational method to compute the global and local solutions of optimization problems. The present hybrid algorithm uses both a genetic algorithm and a local concentrate search algorithm (e. g simplex method). The hybrid algorithm is not only faster than the standard genetic algorithm but also supplies a more accurate solution. In addition, this algorithm can find the global and local optimum solutions. The present algorithm can be supplied to minimize the resonance response (Q factor) and to yield the critical speeds as far from the operating speed as possible. These factors play very important roles in designing a rotor-bearing system under the dynamic behavior constraint. In the present work, the shaft diameter, the bearing length, and clearance are used as the design variables.

• 정보처리학회논문지C
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• 제16C권2호
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• pp.267-274
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• 2009

RFID 리더기가 영역내의 다수의 태그를 인식할 때 태그간의 통신간섭에 의해 태그인식이 방해 받는다. 이를 피하기 위해서는 충돌방지 알고리즘이 필요하게 된다. 충돌방지 알고리즘은 크게 슬롯 알로하 기반 알고리즘과 트리기반 알고리즘으로 나뉜다. 본 논문은 ISO 18000-6 TYPE A에 정의된 알로하 기반의 Framed Slotted ALOHA(FSA) 알고리즘에 태그와 슬롯간의 혼잡도를 이용하여 성능을 개선한 Dynamic Framed Slotted ALOHA-Slot Congestion(DFSA-SC) 알고리즘을 제안한다. 시뮬레이션 결과 최초 태그 수 추정의 정확도를 높여 전체 태그인식 시간이 줄어든 것을 확인 할 수 있었다. 나아가 태그 아이디의 중복성이 클 경우 대표적인 트리기반 알고리즘인 Query Tree 알고리즘보다 제안된 알고리즘이 우수한 것을 확인 할 수 있었다.

• ETRI Journal
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• 제43권2호
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• pp.260-271
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• 2021

This paper addresses Very large-scale integration (VLSI) placement optimization, which is important because of the rapid development of VLSI design technologies. The goal of this study is to develop a hybrid algorithm for VLSI placement. The proposed algorithm includes a sequential combination of a genetic algorithm and an evolutionary algorithm. It is commonly known that local search algorithms, such as random forest, hill climbing, and variable neighborhoods, can be effectively applied to NP-hard problem-solving. They provide improved solutions, which are obtained after a global search. The scientific novelty of this research is based on the development of systems, principles, and methods for creating a hybrid (combined) placement algorithm. The principal difference in the proposed algorithm is that it obtains a set of alternative solutions in parallel and then selects the best one. Nonstandard genetic operators, based on problem knowledge, are used in the proposed algorithm. An investigational study shows an objective-function improvement of 13%. The time complexity of the hybrid placement algorithm is O(N2).

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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• pp.493-496
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• 2003

Recently, Ryu et al. proposed a multiple target DOA tracking algorithm, which has good features that it has no data association problem and simple structure. But its performance is seriously degraded in the low signal-to-noise ratio. In this paper, a measurement fusion method is presented based on ML(Maximum Likelihood), and the new DOA tracking algorithm is proposed by incorporating the presented fusion method into Ryu's algorithm. The proposed algorithm has a better tracking performance than that of Ryu's algorithm, and it sustains the good features of Ryu's algorithm.

• Journal of Advanced Marine Engineering and Technology
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• 제22권4호
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• pp.498-504
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• 1998

This paper presents an optimal control algorithm for the overhead crane. To control the swing motion and the position tracking of the payload of the overhead crane a state feedback control algorithm is applied. by using a hybrid genetic algorithm the feedback gains of the state feedback is optimized to minimize the cost function composed of position errors and payload swing angle under unknown constant disturbances. Computer simulation is performed to demonstrate the effectiveness of the proposed control algorithm.

• 제어로봇시스템학회논문지
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• 제10권7호
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• pp.634-642
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• 2004

Unlike actual vehicles, a vehicle driving simulator is limited in kinematic workspace and bounded on dynamic characteristics. So it is difficult to simulate dynamic motions of a multi-body vehicle model. In order to overcome these problems, a washout algorithm which controls the workspace of the simulator within the kinematic limitation is needed. However, a classical washout algorithm contains several problems such as generation of wrong sensation of motions by filters in tilt coordination, requirement of trial and error method in selecting the proper cut-off frequencies, difficulty in returning the simulator to its origin using only high pass filters and etc. This paper proposes a new tilt coordination method as an algorithm which gives more accurate sensations to drivers. In order to reduce time for returning the simulator to its origin, a new washout algorithm that the proposed algorithm selectively onset mode from high pass filters and return mode from error functions is proposed. As a result of this study, the results of the proposed algorithm are compared with the results of classical washout algorithm through the human perception models. Also, the performance of the suggested algorithm is evaluated by using human perception and sensibility of some drivers through experiments.

• 한국전자통신학회논문지
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• 제7권4호
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• pp.721-726
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• 2012

이 논문에서 SPFA(shortest path faster algorithm)을 사용해서 기존의 벨만-포드(Bellman-Ford)을 개선한 효율적인 알고리듬을 제안한다. 벨만-포드 알고리듬은 딕스트라(Dijkstra) 알고리듬과 다르게 부(-)인 가중치를 갖는 그래프에서 사용할 수 있다. SPFA 알고리듬은 한 대기열을 이용하여 노드를 저장한다. 그래서 중북을 피할 수 있다. 벨만-포드 알고리듬은 시간을 더 사용하여 노드 표를 업데이트를 시킨다. 이 개산 알고리듬에서는 인접 리스트를 이용하여 표의 각 노드를 저장한다. 한 대기열을 통하여 데이트를 저장한다. 개선 방법에서는 새로운 점에 계속 relaxation을 통하여 최적 패스를 얻을 수 있다. 딕스트라 알고리듬과 SPFA 알고리듬과 개선된 알고리듬의 성능을 비교하기 위해서 시뮬레이션을 하였다. 실험 결과에서 랜덤(random) 그래프에서 개선된 알고리듬, SPFA 알고리듬과 딕스트라 알고리듬은 효율이 비슷했었는데, 격자형 지도에서 개선 알고리듬의 효율이 더 높았었다. 처리시간에서 개선된 알고리듬은 SPFA 알고리듬 보다 3분의 2를 감소시켰다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.285-286
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• 2008

In this paper, we propose adaptive search channel estimate algorithm. The proposed algorithm is modified LMS algorithm which has a variable step size and parallel convolution. In simulation result, a error estimate accuracy of the proposed algorithm is about -20 dB and general LMS algorithm is about 10 dB. The proposed algorithm is better error estimate accuracy than general LMS algorithm.