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.
Eric Chen is ready to make a name for himself. American-born Chinese (ABC) and armed with a high-powered banking job, he is destined for success and riches in the world's next superpower. But the New China is rapidly changing, its billion-plus people ambitious, hungry and on the move. Determined to win a take-over deal that sees him shuttle between Shanghai, Beijing, Hong Kong and New York, Eric encounters those also profiting from the world's most promising nation: the playboy son of a Hong Kong tycoon, a hedonistic boss, and another ABC desiring to belong. In the New China, cultural assimilation and confusion, along with temptation and seduction, abound- and Eric could lose himself not to mention those he loves most.
The Yearbook of China's Cultural Industries is a large comprehensive, authoritative and informative annual which accurately records and reflects the annual development of cultural industries in China. It is also a large reference book with abundant information on cultural industries in China and a complex index, which could be kept for a long time and read for many years. A must for libraries. It deals with Radio and TV, the film industry, Press and Publishing Industries, the Entertainment Industry, Online Game Industry, Audio Visual New Media Industry, Advertisement Industry, and the Cultural Tourism Industry. It examines the figures nationally and by region.
One of the first evaluations of China's leadership transition with Jiang Zemin's 2002 retirement as Communist Party chief, this book probes the country's related institutional transitions—both those under way and those still needed if China is to remain stable and prosperous in the 21st century.
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.
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