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A comprehensive review of machine learning‐based methods in landslide susceptibility map**
S Liu, L Wang, W Zhang, Y He, S Pijush - Geological Journal, 2023 - Wiley Online Library
Landslide susceptibility map** (LSM) has been widely used as an important reference for
development and construction planning to mitigate the potential social‐eco impact caused …
development and construction planning to mitigate the potential social‐eco impact caused …
Application of deep learning algorithms in geotechnical engineering: a short critical review
W Zhang, H Li, Y Li, H Liu, Y Chen, X Ding - Artificial Intelligence Review, 2021 - Springer
With the advent of big data era, deep learning (DL) has become an essential research
subject in the field of artificial intelligence (AI). DL algorithms are characterized with powerful …
subject in the field of artificial intelligence (AI). DL algorithms are characterized with powerful …
Prediction of undrained shear strength using extreme gradient boosting and random forest based on Bayesian optimization
Accurate assessment of undrained shear strength (USS) for soft sensitive clays is a great
concern in geotechnical engineering practice. This study applies novel data-driven extreme …
concern in geotechnical engineering practice. This study applies novel data-driven extreme …
[HTML][HTML] Slope stability prediction using ensemble learning techniques: A case study in Yunyang County, Chongqing, China
W Zhang, H Li, L Han, L Chen, L Wang - Journal of Rock Mechanics and …, 2022 - Elsevier
Slope stability prediction plays a significant role in landslide disaster prevention and
mitigation. This study develops an ensemble learning-based method to predict the slope …
mitigation. This study develops an ensemble learning-based method to predict the slope …
[HTML][HTML] State-of-the-art review of soft computing applications in underground excavations
Soft computing techniques are becoming even more popular and particularly amenable to
model the complex behaviors of most geotechnical engineering systems since they have …
model the complex behaviors of most geotechnical engineering systems since they have …
AI-powered landslide susceptibility assessment in Hong Kong
Landslide susceptibility assessment is essential for regional landslide risk assessment and
mitigation. Most past studies involved cell-based analysis that takes landslide incidents as …
mitigation. Most past studies involved cell-based analysis that takes landslide incidents as …
[HTML][HTML] Soft computing approach for prediction of surface settlement induced by earth pressure balance shield tunneling
Estimating surface settlement induced by excavation construction is an indispensable task in
tunneling, particularly for earth pressure balance (EPB) shield machines. In this study …
tunneling, particularly for earth pressure balance (EPB) shield machines. In this study …
[HTML][HTML] Integrated behavioural analysis of FRP-confined circular columns using FEM and machine learning
This study investigates the structural behaviour of double-skin columns, introducing novel
double-skin double filled tubular (DSDFT) columns, which utilise double steel tubes and …
double-skin double filled tubular (DSDFT) columns, which utilise double steel tubes and …
[HTML][HTML] Modelling of shallow landslides with machine learning algorithms
This paper introduces three machine learning (ML) algorithms, the 'ensemble'Random
Forest (RF), the 'ensemble'Gradient Boosted Regression Tree (GBRT) and the MultiLayer …
Forest (RF), the 'ensemble'Gradient Boosted Regression Tree (GBRT) and the MultiLayer …
Stacked LSTM sequence-to-sequence autoencoder with feature selection for daily solar radiation prediction: A review and new modeling results
We review the latest modeling techniques and propose new hybrid SAELSTM framework
based on Deep Learning (DL) to construct prediction intervals for daily Global Solar …
based on Deep Learning (DL) to construct prediction intervals for daily Global Solar …