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 …

Intelligent Transportation Systems (ITSs) are vital for alleviating traffic congestion and
improving traffic efficiency. Due to the delay of network transmission and failure of detectors …

With the emerging electric vehicle (EV) and fast charging technologies, EV load forecasting
has become a concern for planners and operators of EV charging stations (CSs). Due to the …

In recent years, the Intelligent transportations system (ITS) has received considerable
attention, due to higher demands for road safety and efficiency in highly interconnected road …

Traffic flow forecasting is a necessary part in the intelligent transportation systems in
supporting dynamic and proactive traffic control and making traffic management plan …

By develo** cities and increasing population, smart transportation becomes an essential
component of modern societies. Extensive research activities using machine learning …

Civil and military structures are susceptible and vulnerable to damage due to the
environmental and operational conditions. Therefore, the implementation of technology to …

The inconvenience of travel, air pollution and consequent economic losses caused by traffic
congestion have seriously restricted the healthy and sustainable development of cities in …

Short‐term traffic forecasting is becoming more important in intelligent transportation
systems. The k‐nearest neighbour (kNN) method is widely used for short‐term traffic …

To improve the management ability of expressway service area and formulate strategies for
traffic flow changes in time, a short-term traffic flow prediction model is proposed. Firstly …