A Hybrid Feature-Based Autoencoder Model for Predicting Traffic Flow to Accelerate Ambulance Medical Response Time in Internet of Vehicles

Li, Yongmeng; Tian, Yu; Liu, Wenjian; Gao, Longxiang; Tian, Hui; Xing, Lumin

A Hybrid Feature-Based Autoencoder Model for Predicting Traffic Flow to Accelerate Ambulance Medical Response Time in Internet of Vehicles

https://hdl.handle.net/10779/DRO/DU:28252076

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posted on 2025-05-23, 05:26 authored by Yongmeng Li, Yu Tian, Wenjian Liu, Longxiang GaoLongxiang Gao, Hui Tian, Lumin Xing

A Hybrid Feature-Based Autoencoder Model for Predicting Traffic Flow to Accelerate Ambulance Medical Response Time in Internet of Vehicles<p></p>

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DOI - Is version of https://doi.org/10.1109/jiot.2024.3516696

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Piscataway, N.J.

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No

Language

eng

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C1.1 Refereed article in a scholarly journal

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IEEE Internet of Things Journal

Volume

12

Pagination

1-12

ISSN

2327-4662

eISSN

2327-4662

Issue

9

Publisher

IEEE

Publication URL

https://doi.org/10.1109/jiot.2024.3516696

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Bioengineering Machine Learning and Artificial Intelligence Networking and Information Technology R&D (NITRD)3 Good Health and Well Being

A Hybrid Feature-Based Autoencoder Model for Predicting Traffic Flow to Accelerate Ambulance Medical Response Time in Internet of Vehicles

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