• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.885-888
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• 2000

Among the previous searching methods, there are the typical methods such as full search and three-step search, etc. Block motion estimation using exhaustive search is too computationally intensive. To apply in practice, recently proposed fast algorithms have been focused on reducing the computational complexity by limiting the number of searching points. According to the reduction of searching points, the quality performance is aggravated in those algorithms. In this paper, We present a fast and efficient search algorithm for block motion estimation that produces better quality performance and less computational time compared with a three-step search (TSS). Previously the proposed Two Step Search Algorithm (TWSS) by Fang-Hsuan Cheng and San-Nan sun is based on the ideas of dithering pattern for pixel decimation using a part of a block pixels for BMA (Block Matching Algorithm) and multi-candidate to compensate quality performance with several locations. This method has good quality performance at slow moving images, but has bad quality performance at fast moving images. To resolve this problem, the proposed algorithm in this paper considers spatial and temporal correlation using neighbor and previous blocks to improve quality performance. This performance uses neighbor motion vectors and previous motion vectors in addition, thus it needs more searching points. To compensate this weakness, the proposed algorithm uses statistical character of dithering matrix. The proposed algorithm is superior to TWSS in quality performance and has similar computational complexity

• Journal of Information Processing Systems
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• 제16권2호
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• pp.478-493
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• 2020

We designed a new meta-heuristic algorithm named Photon Search Algorithm (PSA) in this paper, which is motivated by photon properties in the field of physics. The physical knowledge involved in this paper includes three main concepts: Principle of Constancy of Light Velocity, Uncertainty Principle and Pauli Exclusion Principle. Based on these physical knowledges, we developed mathematical formulations and models of the proposed algorithm. Moreover, in order to confirm the convergence capability of the algorithm proposed, we compared it with 7 unimodal benchmark functions and 23 multimodal benchmark functions. Experimental results indicate that PSA has better global convergence and higher searching efficiency. Although the performance of the algorithm in solving the optimal solution of certain functions is slightly inferior to that of the existing heuristic algorithm, it is better than the existing algorithm in solving most functions. On balance, PSA has relatively better convergence performance than the existing metaheuristic algorithms.

• 한국정보처리학회논문지
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• 제7권2S호
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• pp.638-648
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• 2000

This paper introduces a new technique for block is matching motion estimation. Since the temporal correlation of the image sequence, the motion vector of a block is highly related to the motion vector of the same coordinate block in the previous image frame. If we can obtain useful and enough information from the motion vector of the same coordinate block of the previous frame, the total number of search points used to find the motion vector of the current block may be reduced significantly. Using that idea, an efficient predicted direction search algorithm (PDSA) for block matching algorithm is proposed. Based on the direction of the blocks of the two successive previous frames, if the direction of the to successive blocks is same, the first search point of the proposed PDSA is moved two pixels to the direction of the block. The searching process after moving the first search point is processed according to the fixed search patterns. Otherwise, full search is performed with search area $\pm$2. Simulation results show that PSNR values are improved up to the 3.4dB as depend on the image sequences and improved about 1.5dB on an average. Search times are reduced about 20% than the other fast search algorithms. Simulation results also show that the performance of the PDSA scheme gives better subjective picture quality than the other fast search algorithms and is closer to that of the FS(Full Search) algorithm.

• Journal of Advanced Marine Engineering and Technology
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• 제40권2호
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• pp.138-145
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• 2016

This paper proposes an improved tabu search method for subset selection in multiple linear regression models. Variable selection is a vital combinatorial optimization problem in multivariate statistics. The selection of the optimal subset of variables is necessary in order to reliably construct a multiple linear regression model. Its applications widely range from machine learning, timeseries prediction, and multi-class classification to noise detection. Since this problem has NP-complete nature, it becomes more difficult to find the optimal solution as the number of variables increases. Two typical metaheuristic methods have been developed to tackle the problem: the tabu search algorithm and hybrid genetic and simulated annealing algorithm. However, these two methods have shortcomings. The tabu search method requires a large amount of computing time, and the hybrid algorithm produces a less accurate solution. To overcome the shortcomings of these methods, we propose an improved tabu search algorithm to reduce moves of the neighborhood and to adopt an effective move search strategy. To evaluate the performance of the proposed method, comparative studies are performed on small literature data sets and on large simulation data sets. Computational results show that the proposed method outperforms two metaheuristic methods in terms of the computing time and solution quality.

• 한국전자거래학회지
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• 제8권2호
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• pp.23-31
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• 2003

링크 기반 검색엔진은사용자의 질의어와 관련된 웹 문서들의 링크 정보를 이용하여 순위를 생성한다. 이러한 링크기반 웹 문서의 특성을 이용한 대표적인 순위 평가 알고리즘. HITS는 웹 페이지들 간의 상호 연결된 링크 정보로부터 웹 문서들의 중요도를 평가하고, 순위 정보에 따른 결과를 제시한다. 이러한 HITS 알고리즘의 문제점은 문서 내의 링크 빈도 수만을 고려하고, 입력 값으로 주어지는 웹 문서 집합의 특성에 의존적이라는 것이다. 본 논문에서는 링크기반 웹 검색 엔진들로부터 얻어진 문서 집합에 대해 질의와 검색결과 간의 적합도를 향상시킨 HITS 알고리즘을 수행하는 검색 에이전트를 설계하였다. 이로써 향상된 검객 성능과 결과의 지역성을 보완한다.

• 한국정보통신학회논문지
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• 제9권8호
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• pp.1649-1655
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• 2005

동위상(I) 파일럿 채널에 할당된 셀룰러 셀 CCSSC와 직교위상(Q) 파일럿 채널에 할당된 핫 스팟 셀 HSCSSC가 공존하는 광대역 OFCDM 시스템에 환경하에서 분리된 I/Q채널 CCSC를 이용한 탐색 알고리즘을 제안하였다. 제안된 알고리즘은 이동 기지국에서 무선 인터넷을 사용하고자 할 때 셀룰러 셀 CCSSC의 영향으로 감소하는 최상의 핫 스팟 셀 HSCSSC을 빠르게 추적하는데 적합하다. 시뮬레이션 결과 제안된 셀 추적 알고리즘이 기존의 셀 추적 알고리즘과 비교하여 훨씬 빠른 결과를 수행할 수 있음을 보였다.

• 한국생산제조학회지
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• 제23권3호
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• pp.213-217
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• 2014

A hybrid search method based on the artificial bee colony algorithm (ABCA) with harmony search (HS) is suggested for finding a global solution in the field of optimization. Three cases of the suggested algorithm were examined for improving the accuracy and convergence rate. The results showed that the case in which the harmony search was implemented with the onlooker phase in ABCA was the best among the three cases. Although the total computation time of the best case is a little bit longer than the original ABCA under the prescribed conditions, the global solution improved and the convergence rate was slightly faster than those of the ABCA. It is concluded that the suggested algorithm improves the accuracy and convergence rate, and it is expected that it can effectively be applied to optimization problems with many design variables and local solutions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권8호
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• pp.3516-3541
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• 2018

Task scheduling is one of the most challenging aspects of cloud computing nowadays, and it plays an important role in improving overall performance in, and services from, the cloud, such as response time, cost, makespan, and throughput. A recent cloud task-scheduling algorithm based on the symbiotic organisms search (SOS) algorithm not only has fewer specific parameters, but also incurs time complexity. SOS is a newly developed metaheuristic optimization technique for solving numerical optimization problems. In this paper, the basic SOS algorithm is reduced, and chaotic local search (CLS) is integrated into the reduced SOS to improve the convergence rate. Simulated annealing (SA) is also added to help the SOS algorithm avoid being trapped in a local minimum. The performance of the proposed SA-CLS-SOS algorithm is evaluated by extensive simulation using the Matlab framework, and is compared with SOS, SA-SOS, and CLS-SOS algorithms. Simulation results show that the improved hybrid SOS performs better than SOS, SA-SOS, and CLS-SOS in terms of convergence speed and makespan.

• 한국항행학회논문지
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• 제25권5호
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• pp.403-408
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• 2021

Harmony Search(HS) 알고리즘은 음악 즉흥 연주 프로세스에서 영감을 받은 메타 휴리스틱 최적화 알고리즘으로 다양한 최적화 문제를 해결하는 데 성공적으로 적용되어 왔다. 본 논문에서는 HS의 성능을 더욱 향상시키기 위해 FSH(Fast Harmony Search) 알고리즘을 제안하였다. 이를 위해 본 논문에서는 HM을 이용하여 목적 변수의 경곗값을 새롭게 정의하여 독립적인 두 개의 화음개선과정을 하나로 통합하는 방법을 제안하였다. 그 결과 알고리즘의 처리 시간이 단축되고 대역폭의 명시적인 결정이 더이상 필요하지 않게 되었다. 또한, 무작위 선택의 활용능력이 향상되었다. 수치적 예시 결과는 제안된 알고리즘이 기존의 HS에 비해 더 나은 해를 찾을 수 있으며 속도 또한 빠르다는 것을 보여준다.

• 한국전자통신학회논문지
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• 제5권4호
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• pp.372-378
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• 2010

시 공간적으로 인접한 주변 블록들의 움직임 정보들을 이용하여 적응적으로 탐색 범위를 조절하는 고속 움직임 추정 기법을 제안한다. 기존의 탐색 범위 조절을 통한 고속 움직임 추정 기법들은 참조 프레임에 있는 모든 블록들의 움직임 벡터들 중에서 최댓값을 이용하여 현재 블록의 탐색 범위 조절을 하기 때문에 움직임이 작은 블록들에 대해서는 최적의 탐색 범위 조절을 못할 수 있다. 본 논문에서는 참조 프레임과 현재 프레임에서 현재 블록과 인접한 주변 블록들의 움직임 정보를 동시에 고려하여 최적의 탐색 범위를 결정하여 움직임 추정을 고속으로 할 수 있는 움직임 추정 기법을 제안한다. 시간적으로 인접된 블록들 즉 참조 프레임에 있는 주변 블록들의 움직임 정보를 이용하면 움직임이 작은 블록의 탐색 범위의 크기를 적절하게 작게 할 수 있어 고속의 움직임 추정을 할 수 있다. 실험을 통하여 본 논문에서 제안한 시 공간적 주변 블록들의 움직임 정보를 이용하는 탐색 범위 조절을 통한 고속 움직임 추정 기법이 비트율과 움직임 추정 오차는 거의 비슷하게 유지하면서 기존의 방법인 Simple Dynamic Search Range(SDSR) 기법보다 탐색 점의 수를 약 15% 더 감소시킬 수 있음을 확인하였다.