Single Block Encoder-Decoder Transformer Model for Multi-Step Traffic Flow Forecasting-Reference-Cited by-同舟云学术

Single Block Encoder-Decoder Transformer Model for Multi-Step Traffic Flow Forecasting

Published:2024-08-10 Issue: Volume: Page:299-304
ISSN:
Container-title:2024 IEEE 6th Symposium on Computers & Informatics (ISCI)
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Author:

Omar Mas¹,Yakub Fitri²,Abu Talip Mohamad Sofian³,Nazmin Maslan Mohd⁴,Sinha Vijay Kumar⁵,Muljono Muljono⁶

Affiliation:

1. Universiti Teknologi Malaysia,WEE Laboratory Malaysia-Japan International Institute of Technology,Kuala Lumpur,Malaysia

2. Universiti Teknologi Malaysia,Malaysia-Japan International Institute of Technology,Department of Electronic System Engineering,Kuala Lumpur,Malaysia

3. University of Malaya,Faculty of Engineering,Department of Electrical Engineering,Kuala Lumpur,Malaysia

4. Universiti Teknikal Malaysia,Faculty of Industrial and Manufacturing Technology and Engineering,Melaka,Malaysia

5. Chitkara University,School of Engineering & Technology,Department of Computer Science & Engineering,Himachal Pradesh,India

6. Universitas Dian Nuswantoro,Faculty of Computer Science,Semarang,Indonesia

Funder

Ministry of Higher Education

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10666969/10667684/10667997.pdf?arnumber=10667997

Reference18 articles.

1. Mitigating Traffic Congestion: The Role of Intelligent Transportation Systems

2. Bibliometric methods in traffic flow prediction based on artificial intelligence

3. Proposal of a Machine Learning Approach for Traffic Flow Prediction

4. Temporal Fusion Transformers for interpretable multi-horizon time series forecasting

5. Convolutional Long-Short Term Memory Network with Multi-Head Attention Mechanism for Traffic Flow Prediction