• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 A
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• pp.446-448
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• 2004

This paper presents an application of parallel hybrid Genetic Algorithm-Tabu Search (GA-TS) algorithm to search an optimal solution of a service restoration in distribution system. In parallel hybrid GA-TS, after GA operations, strings which are not emerged in the past population are selected in the reproduction procedure. After reproduction operation, if there are many strings which are in the past population, we add new random strings into the population. If there's no improvement for the predetermined iteration, local search procedure is executed by f for the strings with high fitness function value. To show the usefulness of the proposed method, developed algorithm has been tested and compared on a practical distribution system in Korea.

• 한국항행학회논문지
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• 제4권1호
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• pp.67-77
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• 2000

본 논문에서는 웨이블렛 변환계수를 이용하여 CELP 부호기의 코드북 탐색 시간을 개선하는 새로운 방법을 제안하고 있다. CELP 음성 부호화기에서 적응 코드북 탐색시 개루프(open loop) 및 폐루프(closed loop) 탐색을 이용하여 피치를 추출하는 과정은 많은 연산량을 필요로 한다. 특히 개루프 탐색에서 전구간에 걸쳐 자기상관함수를 이용한 피치 추출은 과도한 탐색시간에 비효율적인 것으로 지적되어 왔다. 본 논문에서는 다양한 스케일리 계수에 대한 다이애딕 웨이블렛 변환계수의 최대값의 위치가 변하지 않는 주파수에 피치가 존재하는 특성을 이용하여 새로운 적응코드북 탐색 방법을 제안하고 있다. 제안한 알고리즘은 기존의 적응 코드북 탐색 시간을 25% 감소시켰고, 합성된 음성신호의 음질의 차이는 거의 느낄 수 없었다.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2005년도 춘계 종합학술대회 논문집
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• pp.362-368
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• 2005

본 논문은 고속 블록 정합 알고리즘에 관한 것으로, 적응형 육각 탐색에 있어서 차순위 국부 정합점을 이용하여 탐색 패턴을 확장하는 방법에 관한 것이다. 제안된 방법은 고속 움직임 추정의 국부 최소 문제를 경감하기 위해 적응형 육각 탐색의 최적 국부 정합점에 의해 형성된 기존의 탐색 패턴에 차순위 국부 정합점을 중심으로 새롭게 형성한 탐색 패턴을 추가하여 탐색패턴을 적응적으로 확장한다. 제안된 방법에 따르면, 육각 탐색 기반 블록 정합 알고리즘을 확장된 탐색 패턴에 적용하여 움직임 벡터를 추정함으로써 보상 화질 측면에서 개선된 성능을 제공하는 고속 움직임 추정을 수행할 수 있다.

• ETRI Journal
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• 제45권3호
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• pp.418-432
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• 2023

In this work, we proposed a low-complexity hybrid layered tabu-likelihood ascent search (LTLAS) algorithm for large multiple-input multiple-output (MIMO) system. The conventional layered tabu search (LTS) approach involves many partial reactive tabu searches (RTSs), and each RTS requires an initialization and searching phase. In the proposed algorithm, we restricted the upper limit of the number of RTS operations. Once RTS operations exceed the limit, RTS will be replaced by low-complexity likelihood ascent search (LAS) operations. The block-based detection approach is considered to maintain a higher signal-to-noise ratio (SNR) detection performance. An efficient precomputation technique is derived, which can suppress redundant computations. The simulation results show that the bit error rate (BER) performance of the proposed detection method is close to the conventional LTS method. The complexity analysis shows that the proposed method has significantly lower computational complexity than conventional methods. Also, the proposed method can reduce almost 50% of real operations to achieve a BER of 10^-3.

• International Journal of Contents
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• 제2권1호
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• pp.34-38
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• 2006

In this paper, an overview of anti-collision algorithm for RFID system of a standard EPC Class1 protocol is presented, and the binslotted dynamic search algorithm (BDS) based upon the slotted ALOHA and binary tree procedure is proposed and analyzed. Also, the performance is evaluated as comparing the BDS algorithm with the standard bin-slotted algorithm (BSA) through the simulation program. The performance of the proposed BDS algorithm is improved by dynamically identifying the collided-bit position and the collided bins stored in the stack of the reader. As the results, the number of request command that a reader send to tags in the reader s interrogation zone and the total recognition time are decreased to 59% as compared with BSA algorithm. Therefore, the tag identification performance is fairly improved by resolving a collision problem using the proposed BDS algorithm.

• 한국항행학회논문지
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• 제19권6호
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• pp.636-642
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• 2015

본 논문에서는 계단응답으로부터 시 지연을 갖는 선형 연속시스템을 식별하기 위해 HS 최적화 알고리즘을 적용에 관하여 연구하였다. 인식 모델은 1차 시 지연 모델 (FOPDT)로써, FOPDT은 많은 화학 공정과 HAVC 공정에 실효성이 있으며 PID 튜닝에도 적합하다. 최근에 개발된 HS 알고리즘은 완벽한 하모니를 찾아가는 음악적 과정을 개념화 한 것이다. 수학을 기반으로 하는 전통적 기법과 달리 HS는 확률적인 방법을 사용하므로 미분과 같은 수학적 접근을 필요로 하지 않는다. 제시된 인식 방법의 효과를 입증하기 위해 많은 수치 예를 수행하여 결과를 제시하였다.

• Structural Engineering and Mechanics
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• 제65권6호
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• pp.707-719
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• 2018

In this article, a new method is introduced to improve the local search capability of meta-heuristic algorithms using the projection of the path on the border of constraints. In a mathematical point of view, the Gradient Projection Method is applied through a new approach, while the imposed limitations are removed. Accordingly, the gradient vector is replaced with a new meta-heuristic based vector. Besides, the active constraint identification algorithm, and the projection method are changed into less complex approaches. As a result, if a constraint is violated by an agent, a new path will be suggested to correct the direction of the agent's movement. The presented procedure includes three main steps: (1) the identification of the active constraint, (2) the neighboring point determination, and (3) the new direction and step length. Moreover, this method can be applied to some meta-heuristic algorithms. It increases the chance of convergence in the final phase of the search process, especially when the number of the violations of the constraints increases. The method is applied jointly with the authors' newly developed meta-heuristic algorithm, entitled Star Graph. The capability of the resulted hybrid method is examined using the optimal design of truss and frame structures. Eventually, the comparison of the results with other meta-heuristics of the literature shows that the hybrid method is successful in the global as well as local search.

• International Journal of Control, Automation, and Systems
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• 제6권4호
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• pp.571-582
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• 2008

This paper analyzes global convergence of the univariate dynamic encoding algorithm for searches (uDEAS) and provides an application result to function optimization. uDEAS is a more advanced optimization method than its predecessor in terms of the number of neighborhood points. This improvement should be validated through mathematical analysis for further research and application. Since uDEAS can be categorized into the generating set search method also established recently, the global convergence property of uDEAS is proved in the context of the direct search method. To show the strong performance of uDEAS, the global minima of four 30 dimensional benchmark functions are attempted to be located by uDEAS and the other direct search methods. The proof of global convergence and the successful optimization result guarantee that uDEAS is a reliable and effective global optimization method.

• 대한전기학회논문지:전력기술부문A
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• 제48권12호
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• pp.1498-1506
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• 1999

In this paper, a hybridization of Evolutionary Strategy (ES) and a Two-Phase Neural Network(TPNN) is applied to the optimal environmental and economic operation. As the evolutionary computation, ES is to search for the global optimum based on natural selection and genetics but it shows a defect of reducing the convergence rate in the latter part of search, and often does not search the exact solution. Also, neural network theory as a local search technique can be used to search a more exact solution. But it also has the defect that a solution frequently sticks to the local region. So, new algorithm is presented as hybrid methods by combining merits of two methods. The hybrid algorithm has been tested on Emission Constrained Economic Dispatch (ECED) problem and Weighted Emission Economic Dispatch (WEED) problem for optimal environmental and economic operation. The result indicated that the hybrid approach can outperform the other computational efficiency and accuracy.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(II)
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• pp.1434-1437
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• 1987

We present a very simple algorithm for reducing the encoding (codebook search) complexity of vector quantization (VQ), exploiting some features of a vector currently being encoded. A proposed VQ of 16 (=$4{\times}4$) vector dimension and 256 codewords shows a slight performance degradation of about 0.1-0.9 dB, however, with only 16 or 32 among 256 codeword searches, i.e., with just 1/16 or 1/8 search complexity compared to a full-search VQ. And the proposed VQ scheme is also compared to and shown to be a bit superior to tree-search VQ with regard to their SNR performance and memory requirement.