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Chapter
Overview
The failure of slopes has major consequences worldwide, including extensive damage to infrastructure and related economic losses and, in the worst case, loss of life. The ability to monitor and forecast failur...
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Chapter
Real-Time Monitoring and Early Warning of Landslide
The prediction and mitigation of landslide is very challenging worldwide due to its complex nature. An intelligent monitoring and early warning system is a powerful tool for landslide risk reduction. This chap...
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Chapter
Machine Learning Algorithms
This chapter reviews the main machine learning algorithms, as well as the applications in slope engineering analysis including the deformation prediction and the stability assessment via VOSviewer, which is a ...
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Prediction of Slope Stability Using Ensemble Learning Techniques
Slope stability prediction plays a significant role in landslide disaster prevention and mitigation. This chapter develops an ensemble learning-based method to predict the slope stability by introducing the ra...
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Chapter
Future Work Recommendation
Benefited from the great development of AI technologies, more and more ML algorithms have been successfully applied to engineering slope stability assessment in the past decades. Although great achievements ha...
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Chapter
Efficient Seismic Stability Analysis of Slopes Subjected to Water Level Changes Using Gradient Boosting Algorithms
Embankments are widespread throughout the world, and their safety under seismic conditions is a primary concern in the geotechnical engineering community since the failure events may lead to disastrous consequ...
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Chapter
Efficient Time-Variant Reliability Analysis of Bazimen Landslide in the TGRA Using XGBoost and LightGBM
Due to the influences of periodic reservoir water level fluctuation and seasonal rainfall, the reservoir slope reliability may be varying with the external environment. Although geotechnical reliability analys...
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Chapter
Landslide Susceptibility Research Combining Qualitative Analysis and Quantitative Evaluation: A Case Study of Yunyang County in Chongqing, China
Machine learning-based methods are commonly used for landslide susceptibility map**. Most of the recent publications focused on quantitative analysis, i.e., improving data processing methods, comparing and p...
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Chapter
Displacement Prediction of Jiuxian** Landslide Using GRU Networks
Displacement prediction plays a significant role in the landslide disaster early warning. However, landslide deformation is a complex nonlinear dynamic process, posing difficulties in the displacement predicti...
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Chapter
Efficient Reliability Analysis of Slopes in Spatially Variable Soils Using XGBoost
Reliability analysis approach provides a rational means to quantitatively evaluate the safety of geotechnical structures from a probabilistic perspective. However, it suffers from a known criticism of extensiv...
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Chapter
Application of Transfer Learning to Improve Landslide Susceptibility Modeling Performance
This chapter applies the first transfer learning application to landslides susceptibility based on a nationwide dataset and proposed a 1D CNN-bidirectional long short-term memory model on the basis of Landslid...
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Book
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Chapter and Conference Paper
Numerical Analysis on Strut Responses Due to One-Strut Failure for Braced Excavation in Clays
In deep braced excavations in clays, struts and walers play an essential role in the whole supporting system. For multi-level strutting systems, accidental strut failure is possible. Once a single strut fails...
