• Wind and Structures
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• 제29권3호
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• pp.195-207
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• 2019

This paper presents an overview of wind turbine research techniques including the recent application of hybrid testing. Wind turbines are complex structures as they are large, slender, and dynamic with many different operational states, which limits applicable research techniques. Traditionally, numerical simulation is widely used to study turbines while experimental tests are rarer and often face cost and equipment restrictions. Hybrid testing is a relatively new simulation method that combines numerical and experimental techniques to accurately capture unknown or complex behaviour by modelling portions of the structure experimentally while numerically simulating the remainder. This can allow for increased detail, scope, and feasibility in wind turbine tests. Hybrid testing appears to be an effective tool for future wind turbine research, and the few studies that have applied it have shown promising results. This paper presents a literature review of experimental and numerical wind turbine testing, hybrid testing in structural engineering, and hybrid testing of wind turbines. Finally, several applications of hybrid testing for future wind turbine studies are proposed including multi-hazard loading, damped turbines, and turbine failure.

• International Journal of Naval Architecture and Ocean Engineering
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• 제13권1호
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• pp.260-277
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• 2021

The appropriate radiation conditions of ship motion problem with advancing speed in frequency domain are investigated from a theoretical and practical point of view. From extensive numerical experiments that have been conducted for evaluation of the relevant radiation conditions, a hybrid radiation technique is proposed in which the Sommerfeld radiation condition and the free surface damping are mixed. Based on the comparison with the results of the translating and pulsating Green function method, the optimal damping factor of the hybrid radiation technique is selected, and the observed limitations of the proposed hybrid radiation technique are discussed, along with its accuracy obtained from the numerical solutions. Comparative studies of the forward-speed seakeeping prediction methods available confirm that the results of applying the hybrid radiation technique are relatively similar to those obtained from the translating and pulsating Green function method. This confirmation is made in comparisons with the results of solely applying either the free surface damping, or the Sommerfeld radiation condition. By applying the proposed hybrid radiation technique, the wave patterns, hydrodynamic coefficients, and motion responses of the Wigley III hull are finally calculated, and compared with those of model tests. It is found that, in comparison with the model test results, the three-dimensional Rankine source method adopting the proposed hybrid radiation technique is more robust in terms of accuracy and numerical stability, as well as in obtaining the forward speed seakeeping solution.

• 한국음향학회지
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• 제18권1호
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• pp.61-66
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• 1999

본 논문은 화자 적응 방법 제안과 그 방법들의 성능을 검토한 것이다. 본 논문에서 제안 검토한 방법들은 최대사후확률추정(MAPE)방법, 음성 선형 특성을 이용한 방법, 다층 퍼셉트론(MLP)을 이용한 방법과 ARTMAP을 이용한 방법들이다. 각 방법들의 성능 평가를 위하여 한국어 숫자음으로 실험한 결과, 최대사후확률추정 방법과 반연속 HMM의 출력 확률적응, 음성 선형 특성 등 3방법을 결합한 방법이 가장 우수한 결과를 보였으며, 이와 비슷한 실험 결과를 ARTMAP을 이용한 화자 적응 방법에서 보였다.

• 전력전자학회논문지
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• 제26권3호
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• pp.159-166
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• 2021

This study compares the maximum power point tracking (MPPT) control methods of a thermoelectric generator on vehicles. The researchers conduct comparisons on five different MPPT methods, including a fractional open circuit voltage method, a perturbation and observation (P&O) method, an incremental conductance method, a linear extrapolation-based MPPT (LEMPPT) method, and a LEMPPT/P&O hybrid method. These five MPPT methods are theoretically analyzed in detail, and the comparisons are conducted through MATLAB/Simulink simulation results. The comparison outcomes reveal that linear MPPT methods, including LEMPPT and LEMPPT/P&O hybrid methods, are more suitable for a thermoelectric generator on vehicles than the other MPPT methods examined in this work.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2000년도 가을 학술발표회논문집(I)
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• pp.529-534
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• 2000

Hybrid building structure, which comprise both the residential and commercial spaces in a building, are composed of upper shear-walls and lower frames. In these hybrid structures, the structural analysis and design of transfer systems which link upper-wall and lower-frame are crucial. The available structural design methods for the transfer girder are performed by taking a prototype structure, and the details of transfer girder based on these design methods are presented and compared with regard to the dimensions and amount of reinforcements.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.1096-1099
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• 2000

A method to analyze the high speed inter-connects that are composed of frequency dependent lossy distributed lines is presented. Network modeling of hybrid systems is implemented by using the modified nodal admittance matrix in the Laplace transformation domain. The network response is computed by different two methods. One method Is the asymptotic waveform evaluation (AWE) method and other is numerical Laplace inversion method. The merits and demerits of two methods are discussed by applying to several concrete illustrative networks.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.433-439
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• 1998

In this paper, we present an approach to the structure identification based on the input space partition methods and to the parameter identification by hybrid learning method in neuro-fuzzy system. The structure identification can automatically estimate the number of membership function and fuzzy rule using grid partition, tree partition, scatter partition from numerical input-output data. And then the parameter identification is carried out by the hybrid learning scheme using back-propagation and least squares estimate. Finally, we sill show its usefulness for neuro-fuzzy modeling to truck backer-upper control.

• Steel and Composite Structures
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• 제47권6호
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• pp.759-779
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• 2023

The paper proposes two hybrid metaheuristic optimization and artificial neural network (ANN) methods for the close prediction of the ultimate axial compressive capacity of concentrically loaded concrete filled double skin steel tube (CFDST) columns. Two metaheuristic optimization, namely genetic algorithm (GA) and particle swarm optimization (PSO), approaches enable the dynamic training architecture underlying an ANN model by optimizing the number and sizes of hidden layers as well as the weights and biases of the neurons, simultaneously. The former is termed as GA-ANN, and the latter as PSO-ANN. These techniques utilize the gradient-based optimization with Bayesian regularization that enhances the optimization process. The proposed GA-ANN and PSO-ANN methods construct the predictive ANNs from 125 available experimental datasets and present the superior performance over standard ANNs. Both the hybrid GA-ANN and PSO-ANN methods are encoded within a user-friendly graphical interface that can reliably map out the accurate ultimate axial compressive capacity of CFDST columns with various geometry and material parameters.

• 한국경영과학회지
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• 제25권3호
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• pp.125-135
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• 2000

Many different statistical and artificial intelligent techniques have been applied to improve the predictability of credit rating. Hybrid models and systems have also been developed by effectively combining different modeling processes or combining the outcomes of individual models. In this paper, we introduced the rough set theory and developed a hybrid credit rating system that combines individual outcomes in terms of rough set theory. An experiment was conducted to compare the prediction capability of the system with those of other methods. The proposed system based on rough set method outperformed the others.

• 해양환경안전학회지
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• 제5권2호
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• pp.87-97
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• 1999

This study is concerned with developing a hybrid heuristic algorithm for solving the redundancy optimization problem which is very important in system safety, This study develops a HH(Hybrid Heuristic) method combined with two strategies to alleviate the risks of being trapped at a local optimum. One of them is to construct the populations of the initial solutions randomly. The other is the additional search with SA(Simulated Annealing) method in final step. Computational results indicate that HH performs consistently better than the KY method proposed in Kim[8]. Therefore, the proposed HH is believed to an attractive to other heuristic methods.