Traffic Flow Estimation using Machine Learning and 4G/5G Radio Frequency Counters-Reference-Cited by-同舟云学术

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Traffic Flow Estimation using Machine Learning and 4G/5G Radio Frequency Counters

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring)
language:
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Author:

Yaghoubi Forough¹,Catovic Armin²,Gusmao Arthur³,Pieczkowski Jan¹,Boros Peter¹

Affiliation:

1. Ericsson,Stockholm,Sweden

2. EQT Partners,Stockholm,Sweden

3. TRIQ Triathlon,Zurich,Switzerland

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9860273/9860350/09860858.pdf?arnumber=9860858

Reference12 articles.

1. Detection and estimation of road congestion using cellular phones;hansapalangkul;7th International Conference on ITS Telecommunications,2007

2. Traffic Flow Estimation Models Using Cellular Phone Data

3. A survey on LSTM memristive neural network architectures and applications

4. Estimating road traffic congestion from cellular handoff information using cell-based neural networks and K-means clustering

5. Traffic Volume Estimation in Multimodal Urban Networks Using Cell Phone Location Data

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Analytics Use Cases for Landside Traffic Optimization in the Catchment Area of the Airport: Case Study of Zagreb Airport;2023 46th MIPRO ICT and Electronics Convention (MIPRO);2023-05-22

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