Towards future intelligent vehicular network, the machine learning as the promising artificial
intelligence tool is widely researched to intelligentize communication and networking …

Machine learning is widely used to solve networking challenges, ranging from traffic
classification and anomaly detection to network configuration. However, machine learning …

As a powerful tool, the vehicular network has been built to connect human communication
and transportation around the world for many years to come. However, with the rapid growth …

Driven by the demand to accommodate today's growing mobile traffic, 5G is designed to be
a key enabler and a leading infrastructure provider in the information and communication …

It is well-known that numerical weather prediction (NWP) models require considerable
computer power to solve complex mathematical equations to obtain a forecast based on …

In recent years, a plethora of approaches have been proposed to deal with the increasingly
challenging task of multi‐output regression. This study provides a survey on state‐of‐the‐art …

Unlike the conventional neural network theories and implementations, Huang et
al.[Universal approximation using incremental constructive feedforward networks with …

We propose a novel approach for network-wide traffic state prediction where the statistical
time series model ARIMA is used to postprocess the residuals out of the fundamental …

This paper provides an overview of the support vector machine (SVM) methodology and its
applicability to real‐world engineering problems. Specifically, the aim of this study is to …

Accurate time series prediction over long future horizons is challenging and of great interest
to both practitioners and academics. As a well-known intelligent algorithm, the standard …