With the continuous evolution and refinement of urban functional spaces, the escalating
reliance of commuters on public transportation for work-related travel has surged with time …

This paper capitalizes on the increasingly high relevance gained by data-intensive
technologies in the development of intelligent transportation system, which calls for the …

Dockless bike-sharing is becoming popular all over the world, and short-term spatiotemporal
distribution forecasting on system state has been further enlarged due to its dynamic …

Advancements in sensing and the Internet of Things (IoT) technologies generate a huge
amount of data. Mobility on demand (MoD) service benefits from the availability of big data in …

Traffic flow prediction is an integral part of an intelligent transportation system and thus
fundamental for various traffic-related applications. Buses are an indispensable way of …

Accurate short-term forecasting of public transport demand is essential for the operation of
on-demand public transport. Knowing where and when future demands for travel are …

The spatio-temporal prediction task in the transportation network is the core of the solutions
for various traffic problems. On one hand, the mobility pattern in traffic can be reflected in the …

The forecasting of bus passenger flow is important to the bus transit system's operation.
Because of the complicated structure of the bus operation system, it's difficult to explain how …

Manufacturing quality prediction model, as an effective measure to monitor the quality in
advance, has been developed using various data-driven techniques. However, multi …

Accurate PM 2.5 forecasting provides a possibility for establishing an early warning system
to notify the public and take precautionary measures to prevent negative effects on ambient …