• 한국컴퓨터산업학회논문지
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• 제2권4호
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• pp.507-520
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• 2001

압축된 동영상에서 인덱싱을 위한 장면전환 검출기법에서 기존의 방법들은 순차검색, 비순차검색, 모션벡터 등을 이용한다. 본 논문에서는 동영상의 장면전환 검출 속도 및 성능을 개선하기 위해 비순차적 검색 방법을 이용한 Hybrid 기법을 제안하였다. 비순차적 검색방법만으로는 영상의 급격한 변화에는 좋은 결과를 보이지만 점진적으로 변화하는 구간에서는 검출성능이 우수하지 못한 문제가 있다. 이러한 문제를 해결하기 위해 본 논문에서는 급진적인 장면전환검색에는 이진검색기법을 사용하고 점진적인 장면전환검색에서는 분산을 이용하는 Hybrid 알고리즘을 제안하여 검색속도 및 검색성능을 개선하였다. 검색속도는 기존의 순차검색 방법에 비해 10배정도 향상되었다.

• 한국멀티미디어학회논문지
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• 제23권1호
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• pp.31-42
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• 2020

During the 4th Industrial Revolution, service platforms utilizing diverse contents are emerging, and research on recommended systems that can be customized to users to provide quality service is being conducted. hybrid recommendation systems that provide high accuracy recommendations are being researched in various domains, and various filtering techniques, machine learning, and deep learning are being applied to recommended systems. However, in a recommended service environment where data must be analyzed and processed real time, the accuracy of the recommendation is important, but the computational speed is also very important. Due to high level of model complexity, a hybrid recommendation system or a Deep Learning-based recommendation system takes a long time to calculate. In this paper, a Cascade-hybrid recommended algorithm is proposed that can reduce the computational time while maintaining the accuracy of the recommendation. The proposed algorithm was designed to reduce the complexity of the model and minimize the computational speed while processing sequentially, rather than using existing weights or using a hybrid recommendation technique handled in parallel. Therefore, through the algorithms in this paper, contents can be analyzed and recommended effectively and real time through services such as SNS environments or shared economy platforms.

• 한국항행학회논문지
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• 제12권5호
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• pp.483-493
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• 2008

IEEE 802.11 WLAN 표준에 근거한 수신 신호세기 측정치에 기반하여 무선 측위를 수행함에 있어서 이기종 이동기기 수신 감도 문제는 이동기기의 종류가 다양해짐에 따라 중요한 문제로 인식되고 있다. 본 논문에서는 이기종 이동기기 수신 감도 문제를 효과적으로 극복할 수 있는 Hybrid Kriging 알고리즘을 제안하고 시뮬레이션과 실험을 통하여 그 성능을 분석하였다. 시뮬레이션과 실험 결과에 의하면 동일한 기준 측정치가 주어진 경우 제안된 Hybrid Kriging 알고리즘이 현제 널리 활용되고 있는 위치 지문 알고리즘에 비하여 이동기기 수신 신호세기 바이어스가 존재하는 경우에도 보다 더 정확한 위치해를 생성할 수 있음을 알 수 있었다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2000년도 추계학술대회논문집
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• pp.131-142
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• 2000

Facility layout is the early stage of system design that requires a mid-term or long-term plan. Since improper facility layout might incur substantial logistics cost including material handling and re-installment costs, due consideration must be given to decisions on facility layout. Facility layout is concerned with low to arrange equipment necessary for production in a given space. Its objective is to minimize the sum of all the products of each equipment's amount of flow multiplied by distance. Facility layout also is related to the issue of NP-complete, i.e., calculated amounts exponentially increase with the increase of the number of equipment. This study discusses Hybrid GA developed, as an algorithm for facility layout, to solve the above-mentioned problems. The algorithm, which is designed to efficiently place equipment, automatically produces a horizontal passageway by the block, if a designer provides the width and length of the space to be handled. In addition, this study demonstrates the validity of the Algorithm by comparing with existing algorithms that have been developed. We present a Hybrid GA approach to the facility layout problem that improves on existing work in terms of solution quality and method. Experimental results show that the proposed algorithm is able to produce better solution quality and more practical layouts than the ones obtained by applying existing algorithms.

• 한국자동차공학회논문집
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• 제7권6호
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• pp.182-197
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• 1999

Described in this paper is an optimal driving control algorithm which focused on the improvement of fuel economy and the minimization of pollutant emissions in the parallel type hybrid drivertrain system for transit bus. For the energy balance among components such as engine, induction machine and buttery, the algorithm for power split ration determine is proposed. When it is implemented in the hybrid electric control unit(HECU) , using the sub-optimal method and the approximate technique , it is possible to save the memory , to shorten the calculation time, and to achieve the efficient driving actually. A Shift strategy for automated manual transmission is the other side of the driving control algorithm. It enables to select the optimal gear by using several shift maps which were predefined from the proposed method in this paper, As a results of driving simulation, it is proved that these algorithms make the hybrid drivetrain system to reduce fuel consumption and emissions considerably and to have the ability to the efficient use of battery.

• 전기학회논문지P
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• 제67권3호
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• pp.143-148
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• 2018

In this paper, the optimal fuzzy logic controller(FLC) for a hybrid renewable energy system(HRES) is proposed. Generally, hybrid renewable energy systems can consist of wind power, solar power, fuel cells and storage devices. The proposed FLC can effectively control the entire HRES by determining the output power of the fuel cell or the absorption power of the electrolyzer. In general, fuzzy logic controllers can be optimized by classical optimization algorithms such as genetic algorithms(GA) or particle swarm optimization(PSO). However, these FLC have a disadvantage in that their performance varies greatly depending on the control parameters of the optimization algorithms. Therefore, we propose a method to optimize the fuzzy logic controller using the teaching-learning based optimization(TLBO) algorithm which does not have the control parameters of the algorithm. The TLBO algorithm is an optimization algorithm that mimics the knowledge transfer mechanism in a class. To verify the performance of the proposed algorithm, we modeled the hybrid system using Matlab Tool and compare and analyze the performance with other classical optimization algorithms. The simulation results show that the proposed method shows better performance than the other methods.

• ETRI Journal
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• 제37권4호
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• pp.717-726
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• 2015

In this paper, we study an asymmetric two-way relaying network where two source nodes intend to exchange information with the help of multiple relay nodes. A hybrid time-division broadcast relaying scheme with joint relay selection (RS) and power allocation (PA) is proposed to realize energy-efficient transmission. Our scheme is based on the asymmetric level of the two source nodes' target signal-to-noise ratio indexes to minimize the total power consumed by the relay nodes. An optimization model with joint RS and PA is studied here to guarantee hybrid relaying transmissions. Next, with the aid of our proposed intelligent optimization algorithm, which combines a genetic algorithm and a simulated annealing algorithm, the formulated optimization model can be effectively solved. Theoretical analyses and numerical results verify that our proposed hybrid relaying scheme can substantially reduce the total power consumption of relays under a traffic asymmetric scenario; meanwhile, the proposed intelligent optimization algorithm can eventually converge to a better solution.

• 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.

• 한국컴퓨터정보학회논문지
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• 제19권3호
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• pp.55-62
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• 2014

본 논문에서는 기존의 주기적 링크 상태 갱신 기법의 장점인 링크 상태 갱신(Link State Update : LSU) 메시지 수 제어 기능과 적응형 링크 상태 갱신 기법의 장점인 라우팅 성능을 가지는 하이브리드 링크 상태 갱신 기법(Hybrid LSU)을 제안한다. Hybrid LSU 기법은 네트워크 트래픽 정보를 기반으로 임계값이 변하는 적응형 링크 상태 갱신 기법을 가지고 있으며 플로우의 요구 대역폭 정보를 통해 LSU 메시지 전송 중요도를 판단하고 단위 시간 당 업데이트 비율에 따라 LSU 메시지 전송 여부를 판단하여 LSU 메시지 수를 제어할 수 있는 메커니즘을 포함한다. 성능 평가를 위해 기존에 제시된 다양한 LSU 기법과 본 논문에서 제안하는 Hybrid LSU 기법을 MCI 네트워크상에서 라우팅 블록율과 링크 당 평균 LSU 메시지의 개수 등을 성능 평가 항목으로 시뮬레이션 하였다. 그 결과 트래픽 부하가 높아질수록 라우팅 블록율 성능은 그대로 유지하면서 평균 LSU 메시지의 개수를 기존의 적응적 링크 상태 갱신 기법에 비해 10% 정도 줄일 수 있었고 이를 통해 제안하는 기법의 우수성을 확인하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(II)
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• pp.1379-1382
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• 1987

IN ADAPTIVE LINEAR PREDICTION, AN ADAPTIVE CAPABILITY IS BUILT INTO THE PROCESSOR SUCH THAT AS THE IMAGE STATISTICS CHANGE, THE PREDICTION FILTER COEFFICIENTS THEMSELVES CHANGE, PRODUCING A NEW FILTER MORE CLOSELY OPTIMIZED TO THE NEW SET OF IMAGES STATISTICS. THE LMS ALGORITHM MAY BE USED TO ADAPT THE COEFFICIENT OF AN ADAPTIVE PREDICTION FILTER FOR IMAGE SOURCE ENCODING. IN THIS PAPER, TWO CODING SYSTEMS USING DPCM AND LMS ALGORITHMS RESPECTIVELY FOR OBTAINING THE FIRST TRANSFORMED COEFFICIENT IN HYBRID CODING ARE COMPARED.