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As intelligent transportation systems (ITS) approach the realm of widespread deployment, there is an increasing need to robustly capture the variability of link travel time in real-time to generate reliable predictions of real-time traffic conditions. This study proposes an adaptive information fusion model to predict the short-term link travel time distribution by iteratively combining past information on link travel time on the current day with the real-time link travel time information available at discrete time points. The past link travel time information is represented as a discrete distribution. The real-time link travel time is represented as a range, and is characterized using information quality in terms of information accuracy and time delay. A nonlinear programming formulation is used to specify the adaptive information fusion model to update the short-term link travel time distribution by focusing on information quality. The model adapts good information by weighing it higher while shielding the effects of bad information by reducing its weight. Numerical experiments suggest that the proposed model adequately represents the short-term link travel time distribution in terms of accuracy and robustness, while ensuring consistency with ambient traffic flow conditions. Further, they illustrate that the mean of a representative short-term travel time distribution is not necessarily a good tracking indicator of the actual (ground truth) time-dependent travel time on that link. Parametric sensitivity analysis illustrates that information accuracy significantly influences the model, and dominates the effects of time delay and the consistency constraint parameter. The proposed information fusion model bridges key methodological gaps in the ITS deployment context related to information fusion and the need for short-term travel time distributions. 相似文献
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In this paper, a numerical investigation of a float-over installation for an offshore platform is presented to verify the feasibility of the actual installation. The hydrodynamic performance of a T-barge is investigated in the frequency domain, and the coupled motions are analyzed in the time domain. We then compare with those of the model test and determine that the response amplitude operator and the time series agree quite well. The barge exhibits favorable hydrodynamic behavior in the considered sea state, and the equipment loads are allowable. The mooring system and sway fender forces are within the permissible range. Based on these results, we can verify that the actual installation of the offshore platform is feasible. We accurately simulated many important factors and effectively reduced the risk associated with the offshore installation, which is of great importance. As such, we demonstrate that the numerical simulation of the float-over installation for offshore platforms has practical engineering significance. 相似文献
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This paper derives the mathematical expressions for the transit time of cargo through a liner shipping network. Main efforts are devoted to deriving the calculation expressions of the connection time of cargo during trans-shipment. For the forward and many-to-one trans-shipment policies, we conduct a minor correction towards the expressions in existing studies to improve the completeness. Meanwhile, we propose an alternative but more straightforward calculation method for connection time which bypasses the complicated inductive argument in existing studies. Then we introduce two new trans-shipment policies: backward trans-shipment and one-to-many trans-shipment, and mathematically calculate the corresponding connection times. Numerical experiments also deliver some managerial insights into the effectiveness of backward trans-shipment in transit time control. 相似文献
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内置式永磁同步电机(IPMSM)由于其优良的转矩特性和宽广的调速范围而广泛运用于电动汽车电驱系统。与表贴式永磁同步电机(SMPSM)不同,IPMSM转子具有强烈的凸极效应。因此其控制方式相较表贴式更为复杂,需要更加精确的电机数学模型。但是由于饱和效应和交叉耦合,电感参数会随运行工况变化而发生变化,从而影响系统控制精度,所以能够实时掌握内置式永磁同步电机电感参数是非常重要的。本文采用模型参考自适应算法(MRAS)实现IPMSM电感参数在线辨识,运用Runge Kutta离散化方法建立可调模型,依据Popov超稳定性定理推导出自适应律。仿真结果表明,采用MRAS的在线参数辨识算法可以准确、实时地辨识出IPMSM的交、直轴电感。 相似文献
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通过对电动汽车驱动用永磁辅助磁阻同步电动机的转子磁极结构分析,得出不同转子结构对磁阻转矩的影响,在此基础之上,对电机电磁场、转子结构强度和温度场进行仿真分析。仿真结果表明,永磁辅助同步电机的电磁转矩中具有较强的磁阻转矩分量,电机转矩脉动低,安全性好,性价比高,在电动汽车驱动电机中有良好的应用前景。 相似文献
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