Machine Learning in Geohazard Risk Prediction and Assessment: From Microscale Analysis to Regional Mapping presents an overview of the most recent developments in machine learning techniques that have reshaped our understanding of geo-materials and management protocols of geo-risk. The book covers a broad category of research on machine-learning techniques that can be applied, from microscopic modeling to constitutive modeling, to physics-based numerical modeling, to regional susceptibility mapping. This is a good reference for researchers, academicians, graduate and undergraduate students, professionals, and practitioners in the field of geotechnical engineering and applied geology.Introduces machine-learning techniques in the risk management of geo-hazards, particularly recent developmentsCovers a broader category of research and machine-learning techniques that can be applied, from microscopic modeling to constitutive modeling, to physics-based numerical modeling, to regional susceptibility mappingContains contributions from top researchers around the world, including authors from the UK, USA, Australia, Austria, China, and India

Machine Learning in Geohazard Risk Prediction and Assessment: From Microscale Analysis to Regional Mapping presents an overview of the most recent developments in machine learning techniques that have reshaped our understanding of geo-materials and management protocols of geo-risk. The book covers a broad category of research on machine-learning techniques that can be applied, from microscopic modeling to constitutive modeling, to physics-based numerical modeling, to regional susceptibility mapping. This is a good reference for researchers, academicians, graduate and undergraduate students, professionals, and practitioners in the field of geotechnical engineering and applied geology.Introduces machine-learning techniques in the risk management of geo-hazards, particularly recent developmentsCovers a broader category of research and machine-learning techniques that can be applied, from microscopic modeling to constitutive modeling, to physics-based numerical modeling, to regional susceptibility mappingContains contributions from top researchers around the world, including authors from the UK, USA, Australia, Austria, China, and India