Artificial Hummingbird Optimization Algorithm With Hierarchical Deep Learning for Traffic Management in Intelligent Transportation Systems-Reference-Cited by-同舟云学术

Artificial Hummingbird Optimization Algorithm With Hierarchical Deep Learning for Traffic Management in Intelligent Transportation Systems

Published:2024 Issue: Volume:12 Page:17596-17603
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Alruban Abdulrahman¹^ORCID,Mengash Hanan Abdullah²^ORCID,Eltahir Majdy M.³^ORCID,Almalki Nabil Sharaf⁴,Mahmud Ahmed⁵,Assiri Mohammed⁶^ORCID

Affiliation:

1. Department of Information Technology, College of Computer and Information Sciences, Majmaah University, Al Majma’ah, Saudi Arabia

2. Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, Saudi Arabia

3. Department of Information Systems, College of Science & Art at Mahayil, King Khalid University, Jeddah, Saudi Arabia

4. Department of Special Education, College of Education, King Saud University, Riyadh, Saudi Arabia

5. Research Center, Future University in Egypt, New Cairo, Egypt

6. Department of Computer Science, College of Sciences and Humanities at Aflaj, Prince Sattam bin Abdulaziz University, Aflaj, Saudi Arabia

Funder

Deanship of Scientific Research at King Khalid University for funding this work through large group Research

Princess Nourah bint Abdulrahman University Researchers Supporting

Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

Research Supporting

King Saud University, Riyadh, Saudi Arabia

Prince Sattam bin Abdulaziz University

Future University in Egypt

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10379096.pdf?arnumber=10379096

Reference26 articles.

1. On the deployment of V2X roadside units for traffic prediction

2. Inconsistency of AV Impacts on Traffic Flow: Predictions in Literature

3. π-ROAD: a Learn-as-You-Go Framework for On-Demand Emergency Slices in V2X Scenarios

4. Traffic Differentiated Clustering Routing in DSRC and C-V2X Hybrid Vehicular Networks

5. Increased Traffic Flow Through Node-Based Bottleneck Prediction and V2X Communication

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