• 전기학회논문지
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• 제66권12호
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• pp.1782-1791
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• 2017

In this paper, an optimal design of hybrid magnetic levitation(Maglev) system using intelligent optimization algorithms is proposed. The proposed maglev system adopts hybrid suspension system with permanent-magnet(PM) and electro magnet(EM) to reduce the suspension power loss and the teaching-learning based optimization(TLBO) that can overcome the drawbacks of conventional intelligent optimization algorithm is used. To obtain the mathematical model of hybrid suspension system, the magnetic equivalent circuit including leakage fluxes are used. Also, design restrictions such as cross section areas of PM and EM, the maximum length of PM, magnetic force are considered to choose the optimal parameters by intelligent optimization algorithm. To meet desired suspension power and lower power loss, the multi object function is proposed. To verify the proposed object function and intelligent optimization algorithms, we analyze the performance using the mean value and standard error of 10 simulation results. The simulation results show that the proposed method is more effective than conventional optimization methods.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 춘계 학술대회 학술발표 논문집
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• pp.325-329
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• 2003

This paper discuss the method of the system's efficient control using a Intelligent hybrid algorithm in nonlinear dynamics systems. Existing neural network and genetic algorithm for the control of non-linear systems work well in static states. but it be not particularly good in changeable states and must re-learn for the control of the system in the changed state. This time spend a lot of time. For the solution of this problem we suggest the intelligent hybrid self-tuning controller. it includes neural network, genetic algorithm and immune system. it is based on neural network, and immune system and genetic algorithm are added against a changed factor. We will call a change factor an antigen. When an antigen broke out, immune system come into action and genetic algorithm search an antibody. So the system is controled more stably and rapidly. Moreover, The Genetic algorithm use the memory address of the immune bank as a genetic factor. So it brings an advantage which the realization of a hardware easy.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2005년도 추계학술대회 학술발표 논문집 제15권 제2호
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• pp.257-260
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• 2005

This paper discusses a human body extraction method for mobile robot system. The skeleton features are used to analyze human motion and pose estimation. The intelligent robot system requires more robust silhouette extraction method because it has internal vibration and low resolution. The new hybrid silhouette extraction method is proposed to overcome this constrained environment. Finally, the experimental results show the superiority of the Proposed method.

• 제어로봇시스템학회논문지
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• 제14권11호
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• pp.1180-1188
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• 2008

As many systems depend on electronics, concern for fault tolerance is growing rapidly in the safety critical system such as intelligent vehicle. In order to make system fault tolerant, there has been a body of research mainly from aerospace field including predictive hybrid redundancy by Lee. Although the predictive hybrid redundancy has the fault tolerant mechanism to satisfy the fault tolerant requirement of safety crucial system such as x-by-wire system, it suffers form the variability of prediction performance according to the input feature of system. As an alternative to the prediction method of predictive hybrid redundancy for robust fault tolerant, Kalman prediction has attracted some attention because of its well-known and often-used with its structure called Kalman hybrid redundancy. In addition, several numerical simulation results are given where the Kalman hybrid redundancy outperforms with predictive smoothing voter.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.152-152
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• 2000

In this paper, we propose a new approach to intelligent motion and autonomous maneuvering of mobile robots using hybrid system. In high Level, the discrete states are defined by using the sensor-based search windows and the reference motions of a mobile robot as a low vevel are specified in the abstracted motions, The mobile robots can perform both the motion planning and autonomous maneuvering with obstacle avoidance in indoor navigation problem. Simulation and experimental results show that hybrid system approach is an effective method for the autonomous maneuvering in indoor environments.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2007년도 추계학술대회
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• pp.602-609
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• 2007

Combining collaborative filtering with some other technique is most common in hybrid recommender systems. As many recommended items from collaborative filtering seem to be similar with respect to content, the collaborative-content hybrid system suffers in terms of quality recommendation and recommending new items as well. To alleviate such problem, we have developed a novel method that uses a diversity metric to select the dissimilar items among the recommended items from collaborative filtering, which together with the input when fed into content space let us improve and include new items in the recommendation. We present experimental results on movielens dataset that shows how our approach performs better than simple content-based system and naive hybrid system

• 한국지능시스템학회논문지
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• 제15권7호
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• pp.852-857
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• 2005

본 논문은 지능형 로봇 시스템을 위한 인간 몸의 하이브리드 실루엣 추출 기법을 제안한다. 지능형 로봇은 내부적인 진동과 낮은 해상도로 인해 강인한 실루엣 추출을 필요로 한다. 이를 극복하기 위해서 본 논문에서는 하이브리드 실루엣 추출 기법을 제안하였다. 하이브리드 실루엣은 영상간의 공간차 및 시간차 정보를 고려 생성되며 움직임 영역 모델을 통해 두 정보간의 중요성에 가중치를 준다. 최종적으로 실험결과를 통해 제안된 기법의 우수성을 확인하였다.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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• pp.960-968
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• 2005

The high cost in maintaining complex manufacturing process makes it necessary to enhance an efficient maintenance system. For the effective maintenance of manufacturing process, precise fault diagnosis should be performed and an appropriate maintenance action should be executed. This paper suggests an intelligent fault diagnosis system using hybrid data mining. In this system, the rules for the fault diagnosis are generated by hybrid decision tree/genetic algorithm and the most effective maintenance action is selected by decision network and AHP. To verify the proposed intelligent fault diagnosis system, we compared the accuracy of the hybrid decision tree/genetic algorithm with one of the general decision tree learning algorithm(C4.5) by data collected from a coil-spring manufacturing process.

• Structural Engineering and Mechanics
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• 제17권3_4호
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• pp.573-591
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• 2004

A hybrid control system is presented for seismic-resistant building structures with and without soil-structure interaction (SSI). The hybrid control is a damper-actuator-bracing control system composed of passive and active controllers. An intelligent algorithm is developed for the hybrid system, in which the passive damper is designed for minor and moderate earthquakes and the active control is designed to activate when the structural response is greater than a given threshold quantity. Thus, the external energy for active controller can be optimally utilized. In the control of a multistory building, the controller placement is determined by evaluating the optimal location index (OLI) calculated from six earthquake sources. In the study, the soil-structure interaction is considered both in frequency domain and time domain analyses. It is found that the interaction can significantly affect the control effectiveness. In the hybrid control algorithm with intelligent strategy, the working stages of passive and active controllers can be different for a building with and without considering SSI. Thus SSI is essential to be included in predicting the response history of a controlled structure.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2013년도 추계학술발표대회
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• pp.327-328
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• 2013

최근 클라우드 컴퓨팅 환경 내에서 많은 IT 기업들이 그동안에 쌓아두었던 소프트웨어, 하드웨어 기술력을 바탕으로 클라우드 컴퓨팅을 제공하는 데 필요한 IT 인프라 구축에 힘쓰고 있는 시점에서 경쟁력이 심화되고 있다. 그렇기 때문에 대용량의 데이터를 사용자에게 고속으로 제공할 수 있는 방안을 연구하는 것이 클라우드 컴퓨팅 환경에서 대두되고 있는 이슈 중에 하나이다. 본 논문에서는 HSS(Hybrid Storage System) 내부 소프트웨어 시스템 설계 기법에 고속 캐싱을 접목시켜 사용자에게 고속으로 데이터를 제공하는 방안을 제시하였다.