• 한국CDE학회지
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• 제3권3호
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• pp.46-50
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• 1997

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회B
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• pp.2255-2260
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• 2007

This Paper focuses on modeling and simulation to analyze the characteristic of hybrid vehicle. The system includes proton exchange membrane fuel cell(PEMFC), photovoltaic generator(PV), lead-acid battery, motor, vehicle and controller. Main electricity is produced by the PEMFC and battery to meet the requirements of a user load. When vehicle is parked in a sunny place, extra power is generated by the photovotaics and is charged in a battery for next drive. Further we evaluate usefulness of this hybrid vehicle by using ADVISOR - the advanced vehicle simulator written in the Matlab/Simulink environment. According to simulation results, the extra power obtained by photovoltaics which have been explored in nature conditions can help to reduce the electrical load of PEMFC and increase the efficiency (over 30%).

• 전기학회논문지
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• 제61권2호
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• pp.263-269
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• 2012

In order to present that the electromagnetic compatibility standards following the frequency goes up which is based automotive electronics, in this paper, a hybrid/electric vehicle battery which reflects the frequency of the equivalent circuit model is introduced. By using this circuit modeling, the impedance characteristics can be analysed and an analyze of battery one cell is finished. Using this model, each different from the discharging situation, the discharge characteristic curve could be led. Basic theoretical approaches and measuring results through MATLAB and experimental validation of the EIS measurement equipment was used.

• International Journal of Naval Architecture and Ocean Engineering
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• 제10권3호
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• pp.270-281
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• 2018

Application of the LeMoS hybrid (LH) URANS/LES method for the wake parameters prediction is considered. The wake fraction coefficient is calculated for inland ship model M1926 under shallow water conditions and compared to results of PIV measurements. It was shown that due to lack of the resolved turbulence at the interface between LES and RANS zones the artificial grid induced separations can occur. In order to overcome this drawback, a shielding function is introduced into LH model. The new version of the model is compared to the original one, RANS $k-{\omega}$ SST and SST-IDDES models. It is demonstrated that the proposed modification is robust and capable of wake prediction with satisfactory accuracy.

• 정보관리학회지
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• 제19권4호
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• pp.35-51
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• 2002

본 논문에서는 다중 모델 기계학습 기법을 이용하여 자동 문서 분류의 성능과 신뢰도를 향상시킬 수 있는 연구와 실험 결과를 기술하였다. 기존의 다중 모델 기계 학습법들이 훈련 데이터 또는 학습 알고리즘의 편향에 의한 오류를 극복하고자 한 것인데 비해 본 논문에서 제안한 메타 학습을 이용한 하이브리드 다중 모델 방식은 이 두 가지의 오류 원인을 동시에 해소하고자 하였다. 다양한 문서 집합에 대한 실험 결과. 본 논문에서 제안한 하이브리드 다중 모델 학습법이 전반적으로 기존의 일반 다중모델 학습법들에 비해 높은 성능을 보였으며, 다중 모델의 결합 방식으로서 메타 학습이 투표 방식에 비해 효율적인 것으로 나타났다.

• Journal of Information Technology Applications and Management
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• 제15권1호
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• pp.225-242
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• 2008

PM (Inconsistency Pattern Modeling) is a hybrid supervised learning technique using the inconsistence pattern of input variables in mining data sets. The IPM tries to improve prediction accuracy by combining more than two different supervised learning methods. The previous related studies have shown that the IPM was superior to the single usage of an existing supervised learning methods such as neural networks, decision tree induction, logistic regression and so on, and it was also superior to the existing combined model methods such as Bagging, Boosting, and Stacking. The objectives of this paper is explore the characteristics of the IPM. To understand characteristics of the IPM, three experiments were performed. In these experiments, there are high performance improvements when the prediction inconsistency ratio between two different supervised learning techniques is high and the distance among supervised learning methods on MDS (Multi-Dimensional Scaling) map is long.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.155-157
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• 2005

We propose a new category of hybrid multi-layer neural networks with hetero nodes such as Fuzzy Set based Polynomial Neurons (FSPNs) and Polynomial Neurons (PNs). These networks are based on a genetically optimized multi-layer perceptron. We develop a comprehensive design methodology involving mechanisms of genetic optimization and genetic algorithms, in particular. The augmented genetically optimized HFPNN (namely gHFPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional HFPNN. The GA-based design procedure being applied at each layer of HFPNN leads to the selection of preferred nodes (FPNs or PNs) available within the HFPNN. In the sequel, two general optimization mechanisms are explored. First, the structural optimization is realized via GAs whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gHFPNNs quantified through experimentation where we use a number of modeling benchmarks-synthetic and experimental data already experimented with in fuzzy or neurofuzzy modeling.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.408-411
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• 1995

In this paper, we discuss the force control of flexible manipulators. Since the force control of flexible manipulators with planar one or two links using the distributed-parameter modeling has been the subject of a considerable number of publications until now, real time computations of the force control schemes are possible. But, application of those control schemes to multi-link spatial manipulators is fairly complicated. In this paper, we apply a concise hybrid position/force control scheme for a flexible manipulators. We use a lumped-parameter modeling for the flexible manipulators. The Hamilton's principle is applied to derive the equations of motion for the system and then, state-space model is obtained by the Lagrange's method. Finally, comparison of simulation results with experimental results is given to show the performance of our method.

• International Journal of Aeronautical and Space Sciences
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• 제2권1호
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• pp.78-92
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• 2001

In this paper, several dynamic systems are modeled using the time domain finite element method. Galerkins' Weak Principle is used to model the general second-order mechanical system, and is applied to a simple pendulum dynamics. Problems caused by approximating the final momentum are also investigated. Extending the research, some dynamic analysis methods are suggested for the hybrid coordinate systems that have both slew and flexible modes. The proposed methods are based on both Extended Hamilton's Principle and Galerkin's Weak Principle. The matrix wave equation is propagated in space domain, satisfying the geometric/natural boundary conditions. As a result, the flexible motion can be obtained compatible with the applied control input. Numerical example is shown to demonstrate the effectiveness of the proposed modeling methods for the hybrid coordinate systems.

• International Journal of CAD/CAM
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• 제8권1호
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• pp.55-62
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• 2009

Scene Transition Nets(STN) is a very useful modeling method for discrete-continuous hybrid systems. However, it is difficult to write STN in standard object-oriented programming languages because STN programming requires much skill of object-oriented programming and high knowledge of STN of designers. To overcome this problem, the authors have developed a useful GUI simulator software for modeling and simulations of STN. The experimental results of a transport system including an AGV showed the availability of our software.