Stability prediction of a natural and man-made slope using various machine learning algorithms

Application of deep learning algorithms in geotechnical engineering: a short critical review

(2021) Wengang Zhang et al.   ARTIFICIAL INTELLIGENCE REVIEW

A Stability Classification System for the Dragline Dump Slope

(2021) Ashutosh Kumar Bharati et al.   Mining Metallurgy & Exploration

Developing a hybrid model of Jaya algorithm-based extreme gradient boosting machine to estimate blast-induced ground vibrations

(2021) Jian Zhou et al.   INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES

Efficient reliability analysis of earth dam slope stability using extreme gradient boosting method

(2020) Lin Wang et al.   Acta Geotechnica

Modelling of shallow landslides with machine learning algorithms

(2020) Zhongqiang Liu et al.   Geoscience Frontiers

Stability prediction of Himalayan residual soil slope using artificial neural network

(2020) Arunava Ray et al.   NATURAL HAZARDS

Debris Flow Susceptibility Assessment Using the Integrated Random Forest Based Steady-State Infinite Slope Method: A Case Study in Changbai Mountain, China

(2020) Alu Si et al.   Water

Factor of safety of strain-softening slopes

(2020) Hossein Rafiei Renani et al.   Journal of Rock Mechanics and Geotechnical Engineering

Ensemble learning-based classification models for slope stability analysis

(2020) Khanh Pham et al.   CATENA

An artificial neural network approach to inhomogeneous soil slope stability predictions based on limit analysis methods

(2019) Z.G. Qian et al.   SOILS AND FOUNDATIONS

Slope stability prediction for circular mode failure using gradient boosting machine approach based on an updated database of case histories

(2019) Jian Zhou et al.   SAFETY SCIENCE

Machine-Learning-Based Classification Approaches toward Recognizing Slope Stability Failure

(2019) Moayedi et al.   Applied Sciences-Basel

An expert system based on hybrid ICA-ANN technique to estimate macerals contents of Indian coals

(2017) Manoj Khandelwal et al.   Environmental Earth Sciences

Landslide susceptibility mapping using random forest and boosted tree models in Pyeong-Chang, Korea

(2017) Jeong-Cheol Kim et al.   Geocarto International

Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN)

(2017) Bahareh Kalantar et al.   Geomatics Natural Hazards & Risk

Shallow Landslide Susceptibility Modeling Using the Data Mining Models Artificial Neural Network and Boosted Tree

(2017) Hyun-Joo Oh et al.   Applied Sciences-Basel

Slope reliability analysis using surrogate models via new support vector machines with swarm intelligence

(2016) Fei Kang et al.   APPLIED MATHEMATICAL MODELLING

Slope stability analysis using artificial intelligence techniques

(2016) Shakti Suman et al.   NATURAL HAZARDS

Landslide susceptibility mapping using random forest, boosted regression tree, classification and regression tree, and general linear models and comparison of their performance at Wadi Tayyah Basin, Asir Region, Saudi Arabia

(2015) Ahmed Mohamed Youssef et al.   Landslides

Investigation of landslide at Sangaldan near tunnel-47, on Katra- Qazigund railway track, Jammu and Kashmir

(2015) Yudhbir Singh et al.   JOURNAL OF THE GEOLOGICAL SOCIETY OF INDIA

Prediction of minimum factor of safety against slope failure in clayey soils using artificial neural network

(2014) Jamal A. Abdalla et al.   Environmental Earth Sciences

Landslide susceptibility mapping at Vaz Watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF) algorithms

(2013) Mohammad Zare et al.   Arabian Journal of Geosciences

Gradient boosting machines, a tutorial

(2013) Alexey Natekin et al.   Frontiers in Neurorobotics

The prediction of the critical factor of safety of homogeneous finite slopes using neural networks and multiple regressions

(2012) Yusuf Erzin et al.   COMPUTERS & GEOSCIENCES

Classification of slopes and prediction of factor of safety using differential evolution neural networks

(2011) Sarat Kumar Das et al.   Environmental Earth Sciences

Prediction of slope stability using artificial neural network (case study: Noabad, Mazandaran, Iran)

(2009) A. J. Choobbasti et al.   Arabian Journal of Geosciences

Delineation of landslide hazard areas on Penang Island, Malaysia, by using frequency ratio, logistic regression, and artificial neural network models

(2009) Biswajeet Pradhan et al.   Environmental Earth Sciences

Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling

(2009) Biswajeet Pradhan et al.   ENVIRONMENTAL MODELLING & SOFTWARE

Large scale failure of the external waste dump at the “South Field” lignite mine, Northern Greece

(2008) E. Steiakakis et al.   ENGINEERING GEOLOGY

Slope stability analysis: a support vector machine approach

(2008) Pijush Samui   Environmental geology.