Predicting urban travel demand is important in perceiving the future state of a city, deploying
public transportation resources, and building intelligent cities. Influenced by multifarious …

The COVID-19 pandemic is a major global public health problem that has caused hardship
to people's normal production and life. Predicting the traffic revitalization index can provide …

Traffic flow prediction has always been the focus of research in the field of Intelligent
Transportation Systems, which is conducive to the more reasonable allocation of basic …

The complexity of traffic scenarios, the spatial-temporal feature correlations pose higher
challenges for traffic prediction research. Traffic spatial-temporal model is an essential …

The capacity of fully exploiting underlying spatial-temporal dependencies holds the key for
missing traffic data imputation, however, previous studies have neglected the residual …

In recent years, traffic flow prediction has been extensively explored in Intelligent
Transportation Systems, which is beneficial for reducing traffic jams and accidents as well as …

In recent years, the rapid economic development of China, the increase of the urban
population, the continuous growth of private car ownership, the uneven distribution of traffic …

Logistics demand forecasting plays a crucial role in regulating logistics management
activities, develo** production plans, seeking maximum economic returns, and building …

Predicting the nature of each urban functional region based on the transfer rate of empty
cars plays a crucial role in constructing smart cities and urban planning. The transfer rate of …

Traffic flow prediction provides support for travel management, vehicle scheduling, and
intelligent transportation system construction. In this work, a graph space–time network …