With the development of mobile networks, one of the main challenges is performing accurate
prediction in order to maximize resource usage, saving energy and improving quality of …

Mobile data consumption is ever-increasing due to the continuous emergence of bandwidth-
hungry mobile applications as well as the drastic increase in number of mobile terminals …

Road transportation is the largest and complex nonlinear entity of the traffic management
system. Accurate prediction of traffic-related information is necessary for an effective …

Traffic prediction is an important and yet highly challenging problem due to the complexity
and constantly changing nature of traffic systems. To address the challenges, we propose a …

Network traffic prediction is a fundamental prerequisite for dynamic resource provisioning in
wireline and wireless networks, but is known to be challenging due to non-stationarity and …

Today, a significant share of smartphone applications use Artificial Intelligence (AI) elements
that, in turn, are based on Machine Learning (ML) principles. Particularly, ML is also applied …

The increasing amount of traffic in recent years has led to increasingly complex network
problems. To be able to improve overall network performance and increase network …

Short‐term traffic prediction is vital for intelligent traffic systems and influenced by
neighboring traffic condition. Gradient boosting decision trees (GBDT), an ensemble …

Autonomous network traffic prediction will be a key feature in beyond 5G networks. In the
past, researchers have used statistical methods such as Auto Regressive Integrated Moving …

Recently, the demand for realtime and accurate prediction of mobile traffic has been growing
in traffic engineering and dynamic resource allocation that work to handle increased mobile …