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Titlebook: Application of Machine Learning in Slope Stability Assessment; Zhang Wengang,Liu Hanlong,Zhang Yanmei Book 2023 Science Press 2023 Slope S

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发表于 2025-3-21 17:50:05 | 显示全部楼层 |阅读模式
期刊全称Application of Machine Learning in Slope Stability Assessment
影响因子2023Zhang Wengang,Liu Hanlong,Zhang Yanmei
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发行地址Introduces the application of the machine learning and deep learning methods in slope engineering.Presents each method via a slope engineering case history.Encloses some source codes as supplementary
图书封面Titlebook: Application of Machine Learning in Slope Stability Assessment;  Zhang Wengang,Liu Hanlong,Zhang Yanmei Book 2023 Science Press 2023 Slope S
影响因子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 fut
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Application of Machine Learning in Slope Stability Assessment
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Application of Machine Learning in Slope Stability Assessment978-981-99-2756-2
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Book 2023to 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 fut
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Xia Wang,Yi Zhao,Wolfgang A. Halangengineering slopes. This chapter focuses on review of the slope stability analysis methods including the theoretical solutions, numerical simulations, physical experimentations, the in-situ monitoring methods as well as the machine learning approaches.
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