Long-Term Mobile Traffic Forecasting Using Deep Spatio-Temporal Neural Networks-Reference-Cited by-同舟云学术

Long-Term Mobile Traffic Forecasting Using Deep Spatio-Temporal Neural Networks

Published:2018-06-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Eighteenth ACM International Symposium on Mobile Ad Hoc Networking and Computing
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Author:

Zhang Chaoyun¹,Patras Paul¹

Affiliation:

1. School of Informatics

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3209582.3209606

Reference34 articles.

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2. Gianni Barlacchi Marco De Nadai Roberto Larcher Antonio Casella Cristiana Chitic Giovanni Torrisi Fabrizio Antonelli Alessandro Vespignani Alex Pentland and Bruno Lepri. 2015. A multi-source dataset of urban life in the city of Milan and the Province of Trentino. Scientific data 2 (2015). Gianni Barlacchi Marco De Nadai Roberto Larcher Antonio Casella Cristiana Chitic Giovanni Torrisi Fabrizio Antonelli Alessandro Vespignani Alex Pentland and Bruno Lepri. 2015. A multi-source dataset of urban life in the city of Milan and the Province of Trentino. Scientific data 2 (2015).

3. Zhengping Che Sanjay Purushotham Kyunghyun Cho David Sontag and Yan Liu. 2016. Recurrent Neural Networks for Multivariate Time Series with Missing Values. arXiv:1606.01865 (2016). Zhengping Che Sanjay Purushotham Kyunghyun Cho David Sontag and Yan Liu. 2016. Recurrent Neural Networks for Multivariate Time Series with Missing Values. arXiv:1606.01865 (2016).

4. Cisco. 2017. Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update 2016--2021 White Paper. (Februrary 2017). Cisco. 2017. Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update 2016--2021 White Paper. (Februrary 2017).

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