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发表于 2025-3-23 11:34:58 | 显示全部楼层
Short-Term Traffic Speed Prediction via Machine Learnings and behaviors to the traffic congestion. In the past years, traffic speed prediction has been studied a lot and different machine learning methods are employed, including deep learning approaches, which recently attracts much attention from both academic and industry fields. In this work, we inves
发表于 2025-3-23 14:45:44 | 显示全部楼层
A Privacy Preserving Data Collecting Scheme in Vanetd information. In VCS, vehicle information is shared, which necessitates privacy protection. How to balance information sharing and privacy protection is a great challenge. Identity privacy protection is the basic requirement of VCS. In many schemes, pseudonyms are used to protect the vehicle’s iden
发表于 2025-3-23 18:17:03 | 显示全部楼层
An Experimental Method for CAV Dedicated Lane Setting Strategy (CAV) dedicated lane in highway is increased. However, the penetration of CAVs is low at the beginning of this application, and it will increase gradually in the future. Therefore, it is necessary to investigate the setting strategy of the CAV dedicated lane. Here, an experimental method is propose
发表于 2025-3-24 01:54:15 | 显示全部楼层
发表于 2025-3-24 02:36:32 | 显示全部楼层
发表于 2025-3-24 07:37:05 | 显示全部楼层
发表于 2025-3-24 13:50:39 | 显示全部楼层
https://doi.org/10.1057/9780230610484y Neural Network and Extreme Gradient Boost. The training and testing data are collected by ourselves from the California Department of Transportation. Through comparisons with the baseline average method, it is obvious that machine learning approaches can achieve more accurate and stable prediction performance.
发表于 2025-3-24 18:49:57 | 显示全部楼层
https://doi.org/10.1057/9780230107410thout pseudonyms. Furthermore, our scheme supports reputation privacy protection. Finally, security analysis shows that our scheme satisfies the requirement of privacy preserving, and the experiment and performance analysis show our scheme is efficient on computation and communication.
发表于 2025-3-24 21:17:43 | 显示全部楼层
Short-Term Traffic Speed Prediction via Machine Learningy Neural Network and Extreme Gradient Boost. The training and testing data are collected by ourselves from the California Department of Transportation. Through comparisons with the baseline average method, it is obvious that machine learning approaches can achieve more accurate and stable prediction performance.
发表于 2025-3-24 23:34:03 | 显示全部楼层
A Privacy Preserving Data Collecting Scheme in Vanetthout pseudonyms. Furthermore, our scheme supports reputation privacy protection. Finally, security analysis shows that our scheme satisfies the requirement of privacy preserving, and the experiment and performance analysis show our scheme is efficient on computation and communication.
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