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21#
發(fā)表于 2025-3-25 06:20:16 | 只看該作者
https://doi.org/10.1007/978-1-349-12613-2d to set the CAV dedicated lane dynamically according to the traffic flow and the penetration of CAVs. The performance has been evaluated by using Plexe that is a platoon simulation platform. Simulation results show that the proposed method improves traffic flow 25.3% compared with the benchmark method.
22#
發(fā)表于 2025-3-25 11:07:19 | 只看該作者
https://doi.org/10.1007/978-3-030-88185-6ices were used to evaluate the forecasting accuracy. Results show the good accuracy of the method for forecasting traffic volumes in the case study. Based on the results obtained in this paper, it could provide reference for traffic volume forecasting for intelligent transportation systems.
23#
發(fā)表于 2025-3-25 14:33:56 | 只看該作者
An Experimental Method for CAV Dedicated Lane Setting Strategyd to set the CAV dedicated lane dynamically according to the traffic flow and the penetration of CAVs. The performance has been evaluated by using Plexe that is a platoon simulation platform. Simulation results show that the proposed method improves traffic flow 25.3% compared with the benchmark method.
24#
發(fā)表于 2025-3-25 18:56:34 | 只看該作者
25#
發(fā)表于 2025-3-25 23:10:29 | 只看該作者
https://doi.org/10.1007/978-3-662-46756-5lem of traffic velocity missing data recovery as the problem of sparse vectors recovery. Based on a large-scale dataset, we verify the effectiveness of the proposed algorithm. Experimental results show that our STC-CS solution can achieve better recovery performance even if the level of data missing is high.
26#
發(fā)表于 2025-3-26 03:49:30 | 只看該作者
27#
發(fā)表于 2025-3-26 08:21:26 | 只看該作者
28#
發(fā)表于 2025-3-26 11:47:33 | 只看該作者
A Visualization Analysis Approach for Logistics Customer Maintenanceation between continuous features and binary class labels to facilitate classification modeling. A data visualization analysis framework is developed using weight of evidence (WOE), where a semi-supervised approach is proposed to discretize the continuous features for WOE computation targeting on th
29#
發(fā)表于 2025-3-26 14:27:47 | 只看該作者
The Influence of Text Length on Text Classification Modelxt length leads to higher training costs of algorithms. It allows us to find that the common text classification algorithm models have shown significant?influence on the standard English dataset and Reddit mental illness dataset. The length of text or a string, especially for controlling the maximum
30#
發(fā)表于 2025-3-26 19:03:15 | 只看該作者
Roland W. Mitchell,Kirsten T. Edwardsrid. We first investigate the relationship between non-uniform error and query intersection area, and utilize the linear least square to fit the linear relation between them. Then we deduce the optimal partition granularity by minimizing non-uniform error and noise error. In the experiments, we use
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