• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.1975-1988
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• 2019

Short-term traffic flow prediction plays an important role in intelligent transportation systems (ITS) in areas such as transportation management, traffic control and guidance. For short-term traffic flow regression predictions, the main challenge stems from the non-stationary property of traffic flow data. In this paper, we design an ensemble cascading prediction framework based on extremely randomized trees (extra-trees) using a boosting technique called EET to predict the short-term traffic flow under non-stationary environments. Extra-trees is a tree-based ensemble method. It essentially consists of strongly randomizing both the attribute and cut-point choices while splitting a tree node. This mechanism reduces the variance of the model and is, therefore, more suitable for traffic flow regression prediction in non-stationary environments. Moreover, the extra-trees algorithm uses boosting ensemble technique averaging to improve the predictive accuracy and control overfitting. To the best of our knowledge, this is the first time that extra-trees have been used as fundamental building blocks in boosting committee machines. The proposed approach involves predicting 5 min in advance using real-time traffic flow data in the context of inherently considering temporal and spatial correlations. Experiments demonstrate that the proposed method achieves higher accuracy and lower variance and computational complexity when compared to the existing methods.

• Computers and Concrete
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• 제16권5호
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• pp.741-757
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• 2015

In the last decade, several modeling approaches have been proposed and applied to estimate the high-performance concrete (HPC) slump flow. While HPC is a highly complex material, modeling its behavior is a very difficult issue. Thus, the selection and application of proper modeling methods remain therefore a crucial task. Like many other applications, HPC slump flow prediction suffers from noise which negatively affects the prediction accuracy and increases the variance. In the recent years, ensemble learning methods have introduced to optimize the prediction accuracy and reduce the prediction error. This study investigates the potential usage of bagging (Bag), which is among the most popular ensemble learning methods, in building ensemble models. Four well-known artificial intelligence models (i.e., classification and regression trees CART, support vector machines SVM, multilayer perceptron MLP and radial basis function neural networks RBF) are deployed as base learner. As a result of this study, bagging ensemble models (i.e., Bag-SVM, Bag-RT, Bag-MLP and Bag-RBF) are found superior to their base learners (i.e., SVM, CART, MLP and RBF) and bagging could noticeable optimize prediction accuracy and reduce the prediction error of proposed predictive models.

• 설비공학논문집
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• 제13권7호
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• pp.595-601
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• 2001

We applied PIV method to obtain instantaneous and ensemble averaged velocity fields from the first row to the fifth row of a staggered tube bundle. The Reynolds number based on the tube diameter and the maximum velocity was set to be 4,000. Remarkably different natures are observed in the developing bundle flow. Such differences are depicted in the mean recirculating bubble length and the vorticity distributions. The jet-like flow seems to be a dominant feature after the second row and usually skew. However, the ensemble averaged fields show symmetric profiles and the flow characteristics between the third and fourth measuring planes are not so different. comparison between the PIV data and the RANS simulation yields severe disagreement in spite of the same Reynolds number. It can be explained that the distinct jet-like unsteady motions are not to be accounted in th steady numerical analysis.

• 대한기계학회논문집B
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• 제20권7호
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• pp.2289-2297
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• 1996

Flows in the combustion chamber near the spark plug are measured using LDv.A single cylinder DOHC S.I. engine of compression ratio 9.5:1 with a transparent quartz window piston is used. Combustion chamber shape is semi-wedge type. Measured data are analyzed using the ensemble averaged analysis and the cycle resolved analysis which uses FFT Filtering. Turbulent intensity and mean velocity are studied in the main flow direction and the normal to main flow direction as a function of engine speeds. The results shows that the turbulent intensity obtained by the ensemble averaged analysis is greater than that calculated by the cycle resolved analysis. Especially, the ensemble averaged analysis shows increase in turbulence at the end of compression stroke although the cycle resolved analysis shows increase only in the cycle-by-cycle variation with no noticeable increase in turbulence. The mean velocity in the main flow direction increase as engine speed increase. But the mean velocity normal to the main flow does not show such increase. Turbulent intensity in both direction increase in proportion to engine speeds. The magnitude of turbulent intensity is about 0.3 ~ 0.4 times the mean piston speeds at the end of the compression stroke.

• 한국유체기계학회 논문집
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• 제10권4호
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• pp.47-54
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• 2007

Simultaneous 3-D LDV measurements of the in-cylinder flows of three different engine setups were summarized for the quantification of the flow characteristics in each vertical or horizontal plane, and in entire cylinder volume. The ensemble averaged-velocity, tumble and swirl motions, and turbulent kinetic energy during the intake and compression strokes were examined from the measured velocity data (approximately 2,000 points for each engine setup). The better spatial resolution of the 3-D LDV allows measurements of the instantaneous flow structures, yielding more valuable information about the smaller flow structures and the cycle-to-cycle variation of these flow patterns. Tumble and swirl ratios, and turbulent kinetic energy were quantified as planar and volumetric quantities. The measurements and calculation results were animated for the visualization of the flow, and hence ease to analysis.

• 호남수학학술지
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• 제36권1호
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• pp.11-27
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• 2014

In this paper, we propose closures for multi-phase flow models, which satisfy boundary conditions and conservation constraints. The models governing the evolution of the fluid mixing are derived by applying an ensemble averaging procedure to the microphysical equations characterized by distinct phases. We consider compressible multi species multi-phase flow with surface tension and transport.

• 한국물환경학회지
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• 제36권5호
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• pp.353-363
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• 2020

Hydrologic models can be classified into two types: those for understanding physical processes and those for predicting hydrologic quantities. This study deals with how to use the model to predict today's stream flow based on the system's knowledge of yesterday's state and the model parameters. In this regard, for the model to generate accurate predictions, the uncertainty of the parameters and appropriate estimates of the state variables are required. In this study, a relatively simple hydrologic partitioning model is proposed that can explicitly implement the hydrologic partitioning process, and the posterior distribution of the parameters of the proposed model is estimated using the Markov chain Monte Carlo approach. Further, the application method of the ensemble Kalman filter is proposed for updating the normalized soil moisture, which is the state variable of the model, by linking the information on the posterior distribution of the parameters and by assimilating the observed steam flow data. The stochastically and recursively estimated stream flows using the data assimilation technique revealed better representation of the observed data than the stream flows predicted using the deterministic model. Therefore, the ensemble Kalman filter in conjunction with the Markov chain Monte Carlo approach could be a reliable and effective method for forecasting daily stream flow, and it could also be a suitable method for routinely updating and monitoring the watershed-averaged soil moisture.

• 대한기계학회논문집
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• 제18권9호
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• pp.2423-2430
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• 1994

Several factors of the efficient combustion process are shape of combustion chamber, position of spark plug, turbulence flow and so on. the shape of combustion chamber and position of spark plug are constrained to geometrically, and then it could not make a change the shape easily. But the turlence flow in combustion chamber have a great influence on combustion phenomena, and which is much easier to control relatively. And since characteristics of turbulence flow would be very important to the stability of combustion and performances, This study is also essential to future engine-low emission and lean burn engine. This paper shows that the visualization of the turbulence flow of single cylinder engine by using 2way, $45^{\circ}$ inclined and 2 channel hot wire probe through the park plug hole. We also study the characteristics of turbulence flow by means of ensemble averaged mean velocity, turvulence intensity and integral length scale.

• 대한기계학회논문집B
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• 제24권3호
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• pp.382-389
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• 2000

The instantaneous and ensemble averaged flow characteristics of a round jet issuing normally into a crossflow was studied using a flow visualization technique and Particle Image Velocimetry measurements. Experiments were performed at a jet-to-crossflow velocity ratio, 3.3, and two Reynolds numbers, 1050 and 2100, based on crossflow velocity and jet diameter. Instantaneous laser tomographic images of the vertical center plane of the crossflow jet showed that there exist very different natures in the flow structures of the near field jet even though the velocity ratio is the same. It was found that the shear layer becomes much thicker when the Reynolds number is 2100 due to the strong entrainment of the inviscid fluid by turbulent interaction between the jet and crossflow. The mean and second order statistics were calculated by ensemble averaging over 1000 realizations of instantaneous velocity fields. The detail characteristics of mean flow field, stream wise and vertical r.m.s. velocity fluctuations, and Reynolds shear stress distributions were presented. The new PlV results were compared with those from previous experimental and LES studies.

• 대한핵의학회지
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• 제38권6호
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• pp.486-491
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• 2004

목적: 요소분석법. 독립성분분석법 등이 PET을 이용하여 심근혈류를 비침습적으로 측정하기 위하여 사용되어 왔다. 이론적으로 뛰어나고 새로운 방법인 앙상블 독려성분분석법을 이용하여 $H_2^{15}O$ 동적 심근 PET데이터의 정량분석방법을 개발하였다. 이 연구에서 사용한 앙상블 독려성분분석법을 이용하여 환자의 혈류를 정량화 하였다. 대상 및 방법: 관동맥질환이 의심되어 관류 SPECT를 시행한 환자 20명을 대상으로 $H_2^{15}O$ 동적 심근 PET을 시행한 후 앙상블 독립성분분석법을 이용하여 심근 독립성분영상을 추출하였으며, 좌심실영역과 심근영역에 대한 영상대조도를 조사하였다. 앙상블 학습은 독립성분과 가중치 행렬에 대한 확률분포를 가정하고 베이지안 이론에 의해서 혼합자료에 대한 확률분포를 추정한다. 이렇게 추정한 혼합자료의 확률분포와 실제 분포간의 차이인 Kullback-Leibler 발산치가 최소가 되도록 독립성분과 가중치 행렬을 순차적으로 변화시켜가며 최종 해를 찾는 방식이다. 이 연구에서 사후확률분포는 동적 핵의학 영상에 적합한 비음성제약조건과 함께 수정된 가우시안 분포를 이용하여 최적화 하였다. 혈류량은 심첨부, 중벽 네 부분, 하벽 네 부분의 9개 영역으로 나누어 측정하였으며, 측정결과에 대해 관류 SPECT 소견과 관동맥조영술의 소견과 비교하였다. 결과: 전체 20명의 휴식기 및 부하기 영상에서 5명을 제외한 15명의 데이터에 대해 심근혈류를 측정할 수 있었다. $H_2^{15}O$ 동적 심근 PET에서 앙상블 독립성분분석법을 이용하여 정량화한 휴식기 혈류량은 $1.2{\pm}0.40$ ml/min/g, 부하기 혈류량은 $1.85{\pm}1.12$ml/min/g이었다. 같은 영역에 대해 두 번 측정했을 때 측정된 심근혈류값의 상관계수는 0.99로 재현성이 높았다. 분리된 독립성분영상에서 영상대조도는 좌심실에 대한 심근영역의 비는 평균 1:2.7이었다. 관동맥 조영술을 시행한 9명에서 협착이 없는 분절과 협착이 있는 분절의 혈류예비능에 유의한 차이가 있었다(P<0.01). 또한, 관동맥조영술에서 협착이 확인된 66분절의 심근관류 SPECT 소견에서 가역적 혈류감소를 보인 분절의 혈류예비능이 더 많이 감소되는 경향을 보였으나 통계적 유의성을 보이지는 않았다. 결론: 앙상블 학습을 이용한 독립성분분석방법을 이용하여 심근혈류가 측정이 되었다. 앙상블 독립성분분석법을 이용한 $H_2^{15}O$ 동적 심근 PET 분석방법이 관상동맥 질환의 분석 및 동적 핵의학 영상 데이터의 연구에 도움이 될 것으로 기대된다.