Accurate forecasting of citywide traffic flow has been playing critical role in a variety spatial-temporal mining applications, such as intelligent control and public risk assessment. While previous work made significant efforts to learn temporal dynamics spatial dependencies, two key limitations exist current models. First, only the neighboring correlations among adjacent regions are considere...

This paper presents a decision support system for improving the management of intermodal container terminals. It is implemented as a modular architecture which integrates a forecasting model, a planner and a simulation module. While the forecasting module estimates container traffic, the planning module uses this information to generate efficient policies for storage, resource allocation and sc...

Abstract Traffic forecasting has attracted widespread attention recently. In reality, traffic data usually contains missing values due to sensor or communication errors. The Spatio-temporal feature in brings more challenges for processing such values, which the classic techniques (e.g., imputations) are limited: (1) temporal axis, can be randomly consecutively missing; (2) spatial happen on one...