• 한국컴퓨터산업학회논문지
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• 제4권12호
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• pp.1075-1082
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• 2003

본 논문에서는 움직임 추정을 위한 Efficient Center- Biased Hybrid Search (ECBHS) 알고리즘을 제안하였다. 제안된 알고리즘은 Center-Biased Hybrid Search (CBHS) 알고리즘에 기초하고 있다. 제안된 알고리즘은 +, X, 다이아몬드 탐색형태를 결합하여 탐색 윈도우의 중앙으로부터 3pel 이내에 분포하는 움직임 벡터를 찾는 과정에서 탐색점을 효과적으로 감소시킨다. ECBHS는 UCHDS 및 CBHS와 거치 동일한 움직임 추정 정확도를 유지하면서 움직임 추정을 위한 연산량을 효과적으로 감소시킨다. 제안된 알고리즘의 효율성을 실험을 통하여 확인하였다.

• 한국정밀공학회지
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• 제29권12호
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• pp.1304-1312
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• 2012

According to the successful development of hybrid vehicle, hybridization of construction equipments like excavator, wheel loader, and backhoe etc., is gaining increasing attention. However, hybridization of excavator and commercial vehicle is very different. Therefore a specialized energy management control algorithm for excavator should be developed. In this paper, hybridization of excavators is investigated and a new energy management control algorithm is proposed. Four control parameters, i.e., lower baseline, upper baseline, idling generation speed, and idling generation torque, are newly introduced and a new operating principle using those four control parameters is proposed. The use of Genetic Algorithm for the optimization of the four control parameters from the view point of minimization of fuel consumption for standard excavating operation is suggested. In order to verify the proposed algorithm, dedicated simulation program of hybrid excavator was developed. The proposed algorithm is applied to a specific hydraulic excavator and 20.7% improvement of fuel consumption is achieved.

• 제어로봇시스템학회논문지
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• 제17권6호
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• pp.610-618
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• 2011

For improved localization around the indoor/outdoor transit area of buildings, this paper proposes an efficient algorithm combining the measurements from the WLAN (Wireless Local Area Network) and the GPS (Global Positioning System) for. The proposed hybrid localization algorithm considers both multipath errors and NLOS (Non-Line-of-Sight) errors, which occur in most wireless localization systems. To detect and isolate multipath errors occurring in GPS measurements, the propose algorithm utilizes conventional multipath test statistics. To convert WLAN signal strength measurements to range estimates in the presence of NLOS errors, a simple and effective calibration algorithm is designed to compute conversion parameters. By selecting and combining the reliable GPS and WLAN measurements, the proposed hybrid localization algorithm provides more accurate location estimates. An experiment result demonstrates the performance of the proposed algorithm.

• 한국항행학회논문지
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• 제19권2호
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• pp.116-122
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• 2015

지속적으로 증가하고 있는 항공수요에 따라, 공항운영 측면에서 이동지역 내 항공기 이동에 대한 효율성을 증대할 수 있는 방안의 중요성이 대두되고 있다. 본 논문은 공항 이동지역을 운항하는 항공기에게 최단경로를 적시에 제공하여 공항운영의 효율성을 증대시키기 위한 경로 탐색 알고리즘을 제시하고자 한다. 기존 문헌들에서 여러 알고리즘이 개발되었는데, 대표적으로 Dijkstra 알고리즘 $A^*$ 알고리즘이 있다. Dijkstra 알고리즘은 상대적으로 느린 연산속도로 인해 공항구조가 복합해질 경우 최단경로를 적시에 제공하기 어려울 수 있다는 단점이 있으며, $A^*$ 알고리즘은 최적성을 보장하지 못한다는 단점이 있다. 본 논문에서는 두 알고리즘을 병합하여, 각 알고리즘의 단점을 보완한 새로운 Hybrid $A^*$ 알고리즘을 제시하였다. 성능분석 결과, Hybrid $A^*$ 알고리즘은 경로탐색에 있어 빠른 연산속도와 최적성이 개선됨을 확인하였다.

• Journal of Advanced Marine Engineering and Technology
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• 제19권3호
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• pp.99-106
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• 1995

PWM(Pluse Width Modulation) induction motor drives are being used in greater numvers through a wide variety of industrial and commercial applications. In this paper, a new speed control algorithm (hybrid algorithm) for induction motor drives that uses regular sampled PWM and harmonic elimination PWM is presented. The hybrid algorithm in implemeted on the computer to obtain solutions from the calculation equations of the width of the pulses and the firing angles for the selected harmonic elimination. this paper describes the time delay effects and the suitable compensating methods moreover, optical transmission system for driving signals is proposed and is compared with general trnasmission system. The hybrid inverter was tested with induction motor, and these test results are shown that this hybrid inverter closely approximates and exhibits many of the desirable performance characteristic distortions and eliminated the objectionable harmonics. Finally, detailed experimental investigation of the proposed hybrid scheme in presented.

• 한국공작기계학회논문집
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• 제18권2호
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• pp.154-161
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• 2009

In order to implement continuous-path motion on a robot, it is necessary to blend one joint motion to another joint motion near a via point in a trapezoidal form of joint velocity. First, the velocity superposition using parametric interpolation is proposed. Hybrid motion blending is defined as the blending of different two type's motions such as blending of joint motion with linear motion, in the neighborhood of a via point. Second, hybrid motion blending algorithm is proposed based on velocity superposition using parametric interpolation. By using a 3-axis SCARA (Selective Compliance Assembly Robot Arm) robot with $LabVIEW^{(R)}$ $controller^{(1)}$, the velocity superposition algorithm using parametric interpolation is shown to result in less vibration, compared with PTP(Point- To-Point) motion and Kim's algorithm. Moreover, the hybrid motion $algorithm^{(2)}$ is implemented on the robot using $LabVIEW^{(R)(1)}$ programming, which is confirmed by showing the end-effector path of joint-linear hybrid motion.

• 한국인터넷방송통신학회논문지
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• 제17권4호
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• pp.123-128
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• 2017

본 논문은 SMMA (Sliced Multi Modulus Algorithm) 등화 알고리즘에서 등화기의 출력 전력에 비례하는 adaptive modulus와 adaptive stepsize를 적용하므로서 등화 성능을 개선할 수 있는 Hybrid-SMMA 알고리즘에 관한 것이다. 기존 SMMA 알고리즘에서는 등화기의 탭 계수 갱신을 위한 오차 신호를 발생할 때 송신측 신호의 통계 특성치인 modulus를 고정적으로 사용하지만, 제안 Hybrid-SMMA에서는 등화기 출력 신호의 전력에 비례토록 modulus와 오차 신호의 비선형성을 이용하여 stepsize를 적응적으로 변화시킨다. 제안 알고리즘의 개선된 등화 성능을 컴퓨터 시뮬레이션을 통해 확인하였으며, 시뮬레이션 결과 제안 방식이 기존 SMMA보다 모든 성능에서 우월함을 확인하였다.

• Journal of Computing Science and Engineering
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• 제8권4호
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• pp.199-206
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• 2014

The ant colony optimization (ACO) algorithm is a new heuristic algorithm that offers good robustness and searching ability. With in-depth exploration, the ACO algorithm exhibits slow convergence speed, and yields local optimization solutions. Based on analysis of the ACO algorithm and the genetic algorithm, we propose a novel hybrid genetic ant colony optimization (NHGAO) algorithm that integrates multi-population strategy, collaborative strategy, genetic strategy, and ant colony strategy, to avoid the premature phenomenon, dynamically balance the global search ability and local search ability, and accelerate the convergence speed. We select the traveling salesman problem to demonstrate the validity and feasibility of the NHGAO algorithm for solving complex optimization problems. The simulation experiment results show that the proposed NHGAO algorithm can obtain the global optimal solution, achieve self-adaptive control parameters, and avoid the phenomena of stagnation and prematurity.

• 한국지능시스템학회논문지
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• 제14권6호
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• pp.764-770
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• 2004

This paper presents a hybrid data mining mechanism to extract expert knowledge from historical data and extend expert systems' reasoning capabilities by using fuzzy neural network (FNN)-based learning & rule extraction algorithm. Our hybrid data mining mechanism is based on association rule extraction mechanism, FNN learning and fuzzy rule extraction algorithm. Most of traditional data mining mechanisms are depended ()n association rule extraction algorithm. However, the basic association rule-based data mining systems has not the learning ability. Therefore, there is a problem to extend the knowledge base adaptively. In addition, sequential patterns of association rules can`t represent the complicate fuzzy logic in real-world. To resolve these problems, we suggest the hybrid data mining mechanism based on association rule-based data mining, FNN learning and fuzzy rule extraction algorithm. Our hybrid data mining mechanism is consisted of four phases. First, we use general association rule mining mechanism to develop an initial rule base. Then, in the second phase, we adopt the FNN learning algorithm to extract the hidden relationships or patterns embedded in the historical data. Third, after the learning of FNN, the fuzzy rule extraction algorithm will be used to extract the implicit knowledge from the FNN. Fourth, we will combine the association rules (initial rule base) and fuzzy rules. Implementation results show that the hybrid data mining mechanism can reflect both association rule-based knowledge extraction and FNN-based knowledge extension.

• 정보과학회 논문지
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• 제42권5호
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• pp.601-608
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• 2015

미국의 Jeopardy! 퀴즈쇼와 같은 DeepQA 환경에서 인간을 대신해 컴퓨터가 효과적으로 답하기 위해서는, 광범위한 지식 베이스와 빠른 시공간 추론 능력이 요구된다. 본 논문에서는 방향 및 위상 관계 추론을 위한 효율적인 공간 추론 방법 중 하나로, 혼합 공간 추론 알고리즘을 제안한다. 본 알고리즘은 전향 추론과 후향 추론을 결합한 혼합 추론 방식을 취함으로써, 불필요한 추론 계산을 줄여 질의 처리 속도도 향상될 뿐 아니라 공간 지식 베이스의 변화에 효과적인 대처가 가능하도록 설계하였다. 본 연구에서는 이 알고리즘을 기반으로 구현한 혼합 공간 추론기와 샘플 공간 지식베이스를 이용하여 성능 분석 실험들을 수행하였고, 이를 통해 본 논문에서 제안한 혼합 공간 추론 알고리즘의 높은 성능을 확인할 수 있었다.