Tunnel Boring Machines (TBMs) have become prevalent in tunnel construction due to their
high efficiency and reliability. The proliferation of data obtained from site investigations and …

In recent years, the number of wildfires has increased all over the world. Therefore, mapping
wildfire susceptibility is crucial for prevention, early detection, and supporting wildfire …

Shallow tunnels in urban areas are close to adjacent buildings and municipal pipelines.
Ground surface settlement (GSS) due to tunnelling can cause damage to those …

eXplainable artificial intelligence (XAI) methods have emerged to convert the black box of
machine learning (ML) models into a more digestible form. These methods help to …

In recent years, the number of floods around the world has increased. As a result, Flood
Susceptibility Maps (FSMs) became vital for flood prevention, risk mitigation, and decision …

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 …

Nowadays, hybrid soft computing technics are attracting the scholars of construction
materials field due to their high adaptability and prediction performances to data information …

Artificial intelligence (AI), such as machine learning (ML) models, is profoundly impacting an
organization's ability to assess safety risks during the construction of tunnels. Yet, ML …

Occupational accidents are frequent in the construction industry, containing significant risks
in the working environment. Therefore, early designation, taking preventive actions, and …

The frequent occurrence and spread of wildfires pose a serious threat to the ecological
environment and urban development. Therefore, assessing regional wildfire susceptibility is …