Timely maintenance of road pavements is crucial to ensure optimal performance. The
accurate prediction of trends in pavement defects enables more efficient allocation of funds …

In the modern era, the importance of prioritizing traffic safety has become increasingly
evident, requiring dedicated focus. An effective strategy for improving traffic safety involves …

This study is the first attempt to use explainable machine learning (ML) to investigate the
factors influencing physical development and the athlete's performance in the …

This research utilized machine learning to analyze experiments conducted in an open
channel laboratory setting to predict microplastic transport with varying discharge, velocity …

With the dense and huge highway network in China, the highway maintenance
management system has become the most concerned issue for Chinese highway managers …

Pavement condition prediction helps road agencies to schedule maintenance, rehabilitation,
and reconstruction, and to allocate limited funds and resources to such activities. Compared …

This study focuses on accurately predicting rutting depth (RD) through a probabilistic
prediction model, which is crucial for timely road maintenance and traffic safety. Natural …

Prediction of transverse cracking is crucial for pavement practitioners and decision-makers
to prognosticate the cracking development and allocate maintenance budgets. This …

ABSTRACT The Resilient Modulus (MR) is an essential parameter describing the
mechanical behaviour of pavement materials, but the tests to obtain it are time-consuming …

The traditional method for determining the Marshall stability (MS) and Marshall flow (MF) of
asphalt pavements is laborious, time consuming, and costly. This study aims to predict these …