Mingliang Zhou – författare

Artificial intelligence (AI) techniques for rock tunnel construction offer innovative solutions for assessing rock mass quality and ensuring excavation safety in challenging geological conditions. Both cutting-edge contact methods and noncontact methods such as digital photography can provide continuous geological data during excavation. Then, advanced deep learning algorithms for precise characterization of rock face features, along with pioneering multisource 3D data fusion modelling, can enable refined rock mass classification and sophisticated safety evaluation techniques tailored to complex geological environments. By integrating machine vision and intelligent algorithms with rigorous statistical analysis and machine learning models, this book provides practical and refined solutions for the construction industry. It offers improved safety, efficiency, and reliability for tunnel projects and serves as a valuable reference for graduate students and academics.

Artificial intelligence (AI) techniques for rock tunnel construction offer innovative solutions for assessing rock mass quality and ensuring excavation safety in challenging geological conditions. Both cutting-edge contact methods and noncontact methods such as digital photography can provide continuous geological data during excavation. Then, advanced deep learning algorithms for precise characterization of rock face features, along with pioneering multisource 3D data fusion modelling, can enable refined rock mass classification and sophisticated safety evaluation techniques tailored to complex geological environments. By integrating machine vision and intelligent algorithms with rigorous statistical analysis and machine learning models, this book provides practical and refined solutions for the construction industry. It offers improved safety, efficiency, and reliability for tunnel projects and serves as a valuable reference for graduate students and academics.