This book presents basic design theories and principles and provides detailed analysis for excavation failure cases based on the author's research experience, aiming to provide a comprehensive picture of the subject matter. It focuses on the basal heave stability analysis, the apparent earth pressure as well as the strut force determination, the retaining wall deflection, the ground settlement, the protection measures such as jet grouting slabs or piles, case reports, back analysis methodology. From the very basic to the most advanced, it tries to attain theoretical rigorousness and consistency. On the other hand, this book also tries to cope with design practice, implemented by the recent publications from the authors. Students, researchers, and design engineers working in the field of civil engineering could benefit from this book.
This book focuses on the application of machine learning in slope stability assessment. The contents include: overview of machine learning approaches, the mainstream smart in-situ monitoring techniques, the applications of the main machine learning algorithms, including the supervised learning, unsupervised learning, semi- supervised learning, reinforcement learning, deep learning, ensemble learning, etc., in slope engineering and landslide prevention, introduction of the smart in-situ monitoring and slope stability assessment based on two well-documented case histories, the prediction of slope stability using ensemble learning techniques, the application of Long Short-Term Memory Neural Network and Prophet Algorithm in Slope Displacement Prediction, displacement prediction of Jiuxianping landslide using gated recurrent unit (GRU) networks, seismic stability analysis of slopes subjected to water level changes using gradient boosting algorithms, efficient reliability analysis of slopes in spatially variable soils using XGBoost, efficient time-variant reliability analysis of Bazimen landslide in the Three Gorges Reservoir Area using XGBoost and LightGBM algorithms, as well as the future work recommendation.The authors also provided their own thoughts learnt from these applications as well as work ongoing and future recommendations.
This book presents basic design theories and principles and provides detailed analysis for excavation failure cases based on the author's research experience, aiming to provide a comprehensive picture of the subject matter. It focuses on the basal heave stability analysis, the apparent earth pressure as well as the strut force determination, the retaining wall deflection, the ground settlement, the protection measures such as jet grouting slabs or piles, case reports, back analysis methodology. From the very basic to the most advanced, it tries to attain theoretical rigorousness and consistency. On the other hand, this book also tries to cope with design practice, implemented by the recent publications from the authors. Students, researchers, and design engineers working in the field of civil engineering could benefit from this book.
This book focuses on the application of machine learning in slope stability assessment. The contents include: overview of machine learning approaches, the mainstream smart in-situ monitoring techniques, the applications of the main machine learning algorithms, including the supervised learning, unsupervised learning, semi- supervised learning, reinforcement learning, deep learning, ensemble learning, etc., in slope engineering and landslide prevention, introduction of the smart in-situ monitoring and slope stability assessment based on two well-documented case histories, the prediction of slope stability using ensemble learning techniques, the application of Long Short-Term Memory Neural Network and Prophet Algorithm in Slope Displacement Prediction, displacement prediction of Jiuxianping landslide using gated recurrent unit (GRU) networks, seismic stability analysis of slopes subjected to water level changes using gradient boosting algorithms, efficient reliability analysis of slopes in spatially variable soils using XGBoost, efficient time-variant reliability analysis of Bazimen landslide in the Three Gorges Reservoir Area using XGBoost and LightGBM algorithms, as well as the future work recommendation.The authors also provided their own thoughts learnt from these applications as well as work ongoing and future recommendations.
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