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Deep Collaborative Intelligence-Driven Traffic Forecasting in Green Internet of Vehicles

descriptionPublicationkeyboard_double_arrow_right Article 01 Jun 2023 Australia Publisher:Institute of Electrical and Electronics Engineers (IEEE)Journal:IEEE Transactions on Green Communications and Networking, volume 7, pages 1,023-1,035 (eissn: 2473-2400,

Authors: Zhiwei Guo; Keping Yu; Kostromitin Konstantin; Shahid Mumtaz; Wei Wei; Peng Shi; Joel J. P. C. Rodrigues;

doi: 10.1109/tgcn.2022.3193849

Deep Collaborative Intelligence-Driven Traffic Forecasting in Green Internet of Vehicles

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Country

Australia

Related Organizations

Hosei University
Japan
University of Adelaide
Australia
South Ural State University
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RIKEN
Japan
South Ural State University
Russian Federation

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Keywords

GIoV, deep learning, traffic flow forecasting, DGE-TF, road networks, 4611 Machine learning, College of Science and Engineering, computational intelligence

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	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	41
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	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 1%

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Top 10%

Top 1%

Fields of Science (3) View all

engineering and technology

electrical engineering, electronic engineering, information engineering

Fields of Science

engineering and technology

electrical engineering, electronic engineering, information engineering

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Related to Research communities

Energy Research