Traffic congestion forecasting using multilayered deep neural network-Reference-Cited by-同舟云学术

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Traffic congestion forecasting using multilayered deep neural network

Published:2023-05-04 Issue: Volume: Page:1-11
ISSN:1942-7867
Container-title:Transportation Letters
language:en
Short-container-title:Transportation Letters

Author:

Kumar Kranti¹^ORCID,Kumar Manoj²^ORCID,Das Pritikana³^ORCID

Affiliation:

1. Department of Mathematics, Central University of Himachal Pradesh, Dharamshala, India

2. School of Liberal Studies, Dr. B. R. Ambedkar University Delhi, Delhi, India

3. Department of Civil Engineering, Maulana Azad National Institute of Technology, Bhopal, India

Funder

University Grants Commission

Publisher

Informa UK Limited

Subject

Transportation

Link

https://www.tandfonline.com/doi/pdf/10.1080/19427867.2023.2207278

Reference47 articles.

1. A Survey of Road Traffic Congestion Measures towards a Sustainable and Resilient Transportation System

2. Forecasting Traffic Congestion Using ARIMA Modeling

3. Vehicular traffic flow prediction using deployed traffic counters in a city

4. PrePCT: Traffic congestion prediction in smart cities with relative position congestion tensor

5. Artificial intelligence-based vehicular traffic flow prediction methods for supporting intelligent transportation systems

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Fusion of deep belief network and SVM regression for intelligence of urban traffic control system;The Journal of Supercomputing;2024-08-13

2. Predicting vehicle travel time on city streets for trip preplanning and predicting heavy traffic for proactive control of street congestion;Scientific Reports;2024-05-07

3. Construction and Characteristics Analysis of the Xi’an Public Transport Network Considering Single-Mode and Multi-Mode Transferring;Sustainability;2024-05-03

4. Bi-State Prediction Network Model for Mixed Traffic Congestion Prediction;International Journal of Computational Intelligence and Applications;2024-04-25

5. Short-term traffic flow prediction based on vehicle trip chain features;Transportation Letters;2024-04-22

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