Application of machine learning in slope stability assessment / Zhang Wengang, Liu Hanlong, Wang Lin, Zhu Xing, Zhang Yanmei.
Wengang, Zhang, author.; Hanlong, Liu, author.; Lin, Wang, author.; Xing, Zhu, author.; Yanmei, Zhang, author.
2023
TA710
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Title Application of machine learning in slope stability assessment / Zhang Wengang, Liu Hanlong, Wang Lin, Zhu Xing, Zhang Yanmei.
Author Wengang, Zhang, author.
ISBN 9789819927562 (electronic bk.)
9819927560 (electronic bk.)
9819927552
9789819927555
DOI https://doi.org/10.1007/978-981-99-2756-2
Published Singapore : Springer ; Beijing : Science Press, [2023]
Copyright ©2023
Language English
Description 1 online resource (xix, 201 pages) : illustrations (chiefly color)
Other Standard Identifiers 10.1007/978-981-99-2756-2 doi
Call Number TA710
Dewey Decimal Classification 624.1/513630285631
Summary 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.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Source of Description Description based on print version record.
Added Author Hanlong, Liu, author.
Lin, Wang, author.
Xing, Zhu, author.
Yanmei, Zhang, author.
Available in Other Form APPLICATION OF MACHINE LEARNING IN SLOPE STABILITY ASSESSMENT.
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Overview
Remote Sensing Techniques
Machine Learning Algorithms
Real-time Monitoring and Early Warning of Landslide
Prediction of Slope Stability Using Ensemble Learning Techniques
Application of LSTM and Prophet Algorithm in Slope Displacement Prediction
Displacement Prediction of Jiuxianping Landslide using GRU Networks
Efficient 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 TGRA Using XGBoost and LightGBM
Future work recommendation.

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