Identification of rockmass class before construction is crucial to the safe and high-efficiency
building of underground tunnels and has been a challenge for long water diversion tunnels …

Automation of construction machines has grown rapidly in recent years as a response to the
need to increase productivity, increase construction safety, decrease costs, and overcome …

Abstract Water Distribution Networks (WDNs) are susceptible to pipe failures with significant
consequences. Predicting wall-thickness loss in pipes is vital for proactive maintenance and …

Biochar is a carbon-neutral tool for combating climate change. Artificial intelligence
applications to estimate the biochar mitigation effect on greenhouse gases (GHGs) can …

It has become an important research topic to ensure the safe and efficient tunnel boring
machine (TBM) tunneling in the construction of long distance and deep buried tunnels. This …

Spatial prediction of soil ammonia (NH3) plays an important role in monitoring climate
warming and soil ecological health. However, traditional machine learning (ML) models do …

To control tunneling risk, the prediction of the surface settlement rate induced by shield
tunneling using earth pressure balance plays a crucial role. To achieve this, ten …

An accurate and real-time identification of the quality grades of tunnel surrounding rocks is
essential for efficient tunneling and geological hazard prevention when using tunnel boring …

It is important to maintain the safety of road driving by automatically performing a series of
processes to automatically measure and repair damage to the road pavement. However …

Soil water content is an important indicator used to maintain the ecological balance of
farmland. The efficient spatial prediction of soil water content is crucial for ensuring crop …