Travel Time Prediction Using Hybridized Deep Feature Space and Machine Learning Based Heterogeneous Ensemble-Reference-Cited by-同舟云学术

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Travel Time Prediction Using Hybridized Deep Feature Space and Machine Learning Based Heterogeneous Ensemble

Published:2022 Issue: Volume:10 Page:98127-98139
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Chughtai Jawad-Ur-Rehman¹^ORCID,Haq Irfan Ul¹^ORCID,Shafiq Omair²^ORCID,Muneeb Muhammad³^ORCID

Affiliation:

1. Department of Computer and Information Sciences (DCIS), Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad, Pakistan

2. School of Information Technology, Carleton University, Ottawa, Canada

3. Department of Mathematics, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates

Funder

Khalifa University of Science and Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09888138.pdf?arnumber=9888138

Reference74 articles.

1. Deep Transfer Learning for Intelligent Cellular Traffic Prediction Based on Cross-Domain Big Data

2. Travel Time Prediction: Based on Gated Recurrent Unit Method and Data Fusion

3. Travel time prediction with LSTM neural network

4. Short-Term Prediction of Travel Time using Neural Networks on an Interurban Highway

5. The Forecast and the Optimization Control of the Complex Traffic Flow Based on the Hybrid Immune Intelligent Algorithm

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3. Urban Origin–Destination Travel Time Estimation Using K-Nearest-Neighbor-Based Methods;Mathematics;2024-04-20

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