Spatiotemporal modeling and prediction in cellular networks: A big data enabled deep learning approach
In this paper, we propose to leverage the emerging deep learning techniques for
spatiotemporal modeling and prediction in cellular networks, based on big system data …
spatiotemporal modeling and prediction in cellular networks, based on big system data …
Network traffic prediction based on deep belief network in wireless mesh backbone networks
Wireless mesh network is prevalent for providing a decentralized access for users. For a
wireless mesh backbone network, it has obtained extensive attention because of its large …
wireless mesh backbone network, it has obtained extensive attention because of its large …
Performance analysis of network traffic predictors in the cloud
Predicting the inherent traffic behaviour of a network is an essential task, which can be used
for various purposes, such as monitoring and managing the network's infrastructure …
for various purposes, such as monitoring and managing the network's infrastructure …
Forecast on bus trip demand based on ARIMA models and gated recurrent unit neural networks
J Ji, J Hou - … Conference on Computer Systems, Electronics and …, 2017 - ieeexplore.ieee.org
Bus is the most basic trip mode in public transport system. Precise bus trip generation
forecast indicates the short-term number of passengers in each bus station, providing …
forecast indicates the short-term number of passengers in each bus station, providing …
[PDF][PDF] Network Bandwidth Utilization Prediction Based on Observed SNMP Data.
N Rana, KP Bhandari, S Shrestha - Journal of the Institute of …, 2017 - academia.edu
Bandwidth requirement prediction is an important part of network design and service
planning. The natural way of predicting bandwidth requirement for existing network is to …
planning. The natural way of predicting bandwidth requirement for existing network is to …