The rapid development in machine learning and in the emergence of new data sources
makes it possible to examine and predict traffic conditions in smart cities more accurately …

This paper systematically reviews studies that forecast short-term traffic conditions using
spatial dependence between links. We extract and synthesise 130 research papers …

Traffic flow prediction is a critical component of Intelligent Transportation Systems (ITS).
However, the dynamic temporal variations in traffic flow, especially in potential occurrence of …

The accurate short-term passenger flow prediction is of great significance for real-time public
transit management, timely emergency response as well as systematical medium and long …

Traffic forecasting has recently attracted increasing interest due to the popularity of online
navigation services, ridesharing and smart city projects. Owing to the non-stationary nature …

Short-term traffic flow forecasting is a key element in Intelligent Transport Systems (ITS) to
provide proactive traffic state information to road network operators. A variety of methods to …

Despite the exponential transformation occurring in the healthcare industry, operational
failures pose significant challenges in the delivery of safe and efficient care. Incident …

Traffic flow prediction is an important part of the intelligent transportation system. Accurate
multi-step traffic flow prediction plays an important role in improving the operational …

Patient experience is a key quality indicator driven by various patient-and provider-related
factors in healthcare systems. While several studies provided different insights on patient …

Exploring complicated dynamic spatiotemporal correlations has always been a challenging
issue in traffic prediction. Besides, methods that make predictions directly from data with …