Traffic accidents pose a severe global public health issue, leading to 1.19 million fatalities
annually, with the greatest impact on individuals aged 5 to 29 years old. This paper …

A complex AI system must be worked offline because the training and execution phases are
processed separately. This process often requires different computer resources due to the …

In large-scale traffic optimization, models based on Macroscopic Fundamental Diagram
(MFD) are recognized for their efficiency in broad analyses. However, they fail to reflect …

In contemporary society, the rapid progression of urbanization and technological
advancements has led to a substantial increase in the number of vehicles, consequently …

This study aims to identify the factors that influence the occurrence of traffic accidents to
improve motorway traffic safety. Various data, including the frequency of traffic accidents …

Background/Objectives: This paper presents a Residual Neural Network (ResNet) based
framework tailored for structured traffic accident data, aiming to improve accident severity …

Vehicle simulation algorithms play a crucial role in enhancing traffic efficiency and safety by
predicting and evaluating vehicle behavior in various traffic scenarios. Recently, vehicle …

Accurate forecasting of solar irradiance and photovoltaic (PV) power generation is critical for
optimizing renewable energy integration and enhancing energy management systems. This …

Deep learning must be worked offline because the training and execution phases are
processed separately. This process often requires different computers due to the …