Short-term traffic flow prediction plays a key role of Intelligent Transportation System (ITS),
which supports traffic planning, traffic management and control, roadway safety evaluation …

In recent years, the Intelligent transportations system (ITS) has received considerable
attention, due to higher demands for road safety and efficiency in highly interconnected road …

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 …

As one of the most important applications of industrial Internet of Things, intelligent
transportation system aims to improve the efficiency and safety of transportation networks. In …

Short-term traffic flow forecasting at isolated points is a fundamental yet challenging task in
many intelligent transportation systems. We present a novel long short-term memory (LSTM) …

Due to the characteristics of time-varying traffic and nonlinearity, the short-term traffic flow
data are difficult to predict accurately. The purpose of this paper is to improve the short-term …

Time series forecasting is important in many aspects of our lives, since it can be used to deal
with the uncertainty to further support the decision making. Despite many advanced …

Short-term traffic flow forecasting is a fundamental and challenging task due to the stochastic
dynamics of the traffic flow, which is often imbalanced and noisy. This paper presents a …

This study delves into the application of Graph Neural Networks (GNNs) in the realm of traffic
forecasting, a crucial facet of intelligent transportation systems. Accurate traffic predictions …

Data-driven soft modeling has been extensively used for industrial processes to estimate
key quality indicators which are hard to measure by some physical devices. However, the …