Artificial neural network (ANN) has acquired noticeable interest from the research
community to handle complex problems in Construction and Building engineering (CB). This …

Predicting traffic states has gained more attention because of its practical significance.
However, the existing literature lacks a critical review regarding how to address the …

Deep Learning methods have been proven to be flexible to model complex phenomena.
This has also been the case of Intelligent Transportation Systems, in which several areas …

The accurate forecasting of traffic states is an essential application of intelligent
transportation system. Due to the periodic signal control at intersections, the traffic flow in an …

Network traffic flow prediction on a fine-grained spatio-temporal scale is essential for
intelligent transportation systems, and extensive studies have been carried out in this area …

Short-term passenger flow prediction has practical significance for metro management and
operation. However, the complex nonlinear and non-stationary characteristics make it …

Traffic forecasting is a particularly challenging and important application direction in the field
of spatial–temporal prediction. However, it is difficult for existing models to accurately …

The structural health monitoring system (SHM) of long-span bridges inevitably produces low-
quality data. It is important to evaluate the data quality and screen out normal data. Most …

Accurate prediction of the future trajectories of traffic agents is a critical aspect of
autonomous vehicle navigation. However, most existing approaches focus on predicting …

Short-term traffic flow prediction is a significant and challenging research topic as it is closely
related to the application of intelligent transportation systems. Due to the variable and …