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

journal contribution

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

History

Journal

IEEE Internet of Things Journal

Volume

12

Pagination

1-12

Location

Piscataway, N.J.

Open access

No

ISSN

2327-4662

eISSN

2327-4662

Language

eng

Publication classification

C1.1 Refereed article in a scholarly journal

Issue

9

Publisher

IEEE

Publication URL

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

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Keywords

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

History

Journal

Volume

Pagination

Location

Open access

ISSN

eISSN

Language

Publication classification

Issue

Publisher

Publication URL

Usage metrics

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Keywords

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