Short-term origin–destination (OD) flow prediction in urban rail transit (URT) plays a crucial
role in smart and real-time URT operation and management. Different from other short-term …

An accurate origin–destination (OD) passenger flow prediction system is crucially important
for urban metro operation and management. However, there are still lacking targeted …

Forecasting short-term ridership of different origin-destination pairs (ie, OD matrix) is crucial
to the real-time operation of a metro system. However, this problem is notoriously difficult …

Network-wide short-term inflow prediction is important in efficiently managing the urban
transportation system. Nowadays, all kinds of traffic modes gradually become …

Origin-destination (OD) short-term passenger flow forecasting (OD STPFF) in urban rail
transit (URT) is essential for develo** timely network measures. The capacity utilization …

High-density land uses cause high-intensity traffic demand. Metro as an urban mass transit
mode is considered as a sustainable strategy to balance the urban high-density land uses …

Short-term Origin-Destination (OD) matrix prediction in metro systems aims to predict the
number of passenger demands from one station to another during a short time period. That …

The short-term passenger flow prediction of the urban rail transit (URT) system is of great
significance for traffic operation and management. Emerging deep learning-based models …

Accurate prediction of short-term origin-destination (OD) matrix is crucial for operations in
metro systems. Recently, some deep learning-based models have been proposed for OD …

Accurate prediction of short-term passengers' origin and destination (OD) demands is key to
efficient operation and management of urban rail transit (URT), especially in the case of …