Traffic prediction plays a crucial role in alleviating traffic congestion which represents a
critical problem globally, resulting in negative consequences such as lost hours of additional …

In recent decades, the development of transport infrastructure has had a great development,
although traffic problems continue to spread due to increase due to the increase in the …

Since many real world networks are evolving over time, such as social networks and user-
item networks, there are increasing research efforts on dynamic network embedding in …

Accurate forecasting of future traffic flow has a wide range of applications, which is a
fundamental component of intelligent transportation systems. However, timely and accurate …

Short-term traffic flow forecasting at isolated points is a fundamental yet challenging task in
many intelligent transportation systems. We present a novel long short-term memory (LSTM) …

Timely and accurate traffic flow forecasting is open challenging. Canonical long short-term
memory (LSTM) network is considered qualified to capture the long-term temporal …

The complex traffic network spatial correlation and the characteristic of high nonlinear and
dynamic traffic conditions in the time are the challenges to accurate traffic flow forecasting …

Balancing network traffic among base stations poses a primary challenge for mobile
operators because of the escalating demand for enhanced data speeds in large-scale 5G …

Smart cities are urban areas that utilize digital solutions to enhance the efficiency of
conventional networks and services for sustainable growth, optimized resource …

Traffic prediction is critical to expanding a smart city and country because it improves urban
planning and traffic management. This prediction is very challenging due to the multifactorial …