Deep Collaborative Intelligence-Driven Traffic Forecasting in Green Internet of Vehicles
出版年份 2022 全文链接
标题
Deep Collaborative Intelligence-Driven Traffic Forecasting in Green Internet of Vehicles
作者
关键词
-
出版物
IEEE Transactions on Green Communications and Networking
Volume 7, Issue 2, Pages 1023-1035
出版商
Institute of Electrical and Electronics Engineers (IEEE)
发表日期
2022-07-27
DOI
10.1109/tgcn.2022.3193849
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- Spatio-Temporal Feature Encoding for Traffic Accident Detection in VANET Environment
- (2022) Zhili Zhou et al. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- A Collaborative V2X Data Correction Method for Road Safety
- (2022) Liang Zhao et al. IEEE TRANSACTIONS ON RELIABILITY
- Deep-Learning-Empowered Breast Cancer Auxiliary Diagnosis for 5GB Remote E-Health
- (2021) Keping Yu et al. IEEE WIRELESS COMMUNICATIONS
- Graph embedding‐based intelligent industrial decision for complex sewage treatment processes
- (2021) Zhiwei Guo et al. INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
- A data-driven intelligent planning model for UAVs routing networks in mobile Internet of Things
- (2021) Dian Meng et al. COMPUTER COMMUNICATIONS
- Fuzzy Detection System for Rumors Through Explainable Adaptive Learning
- (2021) Zhiwei Guo et al. IEEE TRANSACTIONS ON FUZZY SYSTEMS
- Secure Artificial Intelligence of Things for Implicit Group Recommendations
- (2021) Keping Yu et al. IEEE Internet of Things Journal
- Deep Learning-Embedded Social Internet of Things for Ambiguity-Aware Social Recommendations
- (2021) Zhiwei Guo et al. IEEE Transactions on Network Science and Engineering
- Spatial temporal incidence dynamic graph neural networks for traffic flow forecasting
- (2020) Hao Peng et al. INFORMATION SCIENCES
- Reinforced Spatiotemporal Attentive Graph Neural Networks for Traffic Forecasting
- (2020) Fan Zhou et al. IEEE Internet of Things Journal
- Collaborative Learning of Communication Routes in Edge-Enabled Multi-Access Vehicular Environment
- (2020) Celimuge Wu et al. IEEE Transactions on Cognitive Communications and Networking
- Optimized Graph Convolution Recurrent Neural Network for Traffic Prediction
- (2020) Kan Guo et al. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- Multi-stage attention spatial-temporal graph networks for traffic prediction
- (2020) Xueyan Yin et al. NEUROCOMPUTING
- Traffic flow prediction over muti-sensor data correlation with graph convolution network
- (2020) Wei Li et al. NEUROCOMPUTING
- Variational Graph Neural Networks for Road Traffic Prediction in Intelligent Transportation Systems
- (2020) Fan Zhou et al. IEEE Transactions on Industrial Informatics
- A Deep Graph Neural Network-Based Mechanism for Social Recommendations
- (2020) Zhiwei Guo et al. IEEE Transactions on Industrial Informatics
- Decentralized Radio Resource Adaptation in D2D-U Networks
- (2020) Rui Yin et al. IEEE Internet of Things Journal
- Temporal Multi-Graph Convolutional Network for Traffic Flow Prediction
- (2020) Mingqi Lv et al. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- Deep Learning-Based Traffic Safety Solution for a Mixture of Autonomous and Manual Vehicles in a 5G-Enabled Intelligent Transportation System
- (2020) Keping Yu et al. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- Topological Graph Convolutional Network-Based Urban Traffic Flow and Density Prediction
- (2020) Han Qiu et al. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- QoS-Guarantee Resource Allocation for Multibeam Satellite Industrial Internet of Things With NOMA
- (2019) Xin Liu et al. IEEE Transactions on Industrial Informatics
- Spatio-Temporal Wireless Traffic Prediction with Recurrent Neural Network
- (2018) Chen Qiu et al. IEEE Wireless Communications Letters
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