Application of artificial intelligence in geotechnical engineering: A state-of-the-art review

A Baghbani, T Choudhury, S Costa, J Reiner - Earth-Science Reviews, 2022 - Elsevier
Geotechnical engineering deals with soils and rocks and their use in engineering
constructions. By their nature, soils and rocks exhibit complex behaviours and a high level of …

Landslide Susceptibility mapping using random forest and extreme gradient boosting: A case study of Fengjie, Chongqing

W Zhang, Y He, L Wang, S Liu, X Meng - Geological Journal, 2023 - Wiley Online Library
Landslide susceptibility analysis can provide theoretical support for landslide risk
management. However, some susceptibility analyses are not sufficiently interpretable …

[HTML][HTML] GIS-based landslide susceptibility modeling: A comparison between fuzzy multi-criteria and machine learning algorithms

SA Ali, F Parvin, J Vojteková, R Costache, NTT Linh… - Geoscience …, 2021 - Elsevier
Hazards and disasters have always negative impacts on the way of life. Landslide is an
overwhelming natural as well as man-made disaster that causes loss of natural resources …

[HTML][HTML] Spatial prediction of landslide susceptibility in western Serbia using hybrid support vector regression (SVR) with GWO, BAT and COA algorithms

AL Balogun, F Rezaie, QB Pham, L Gigović… - Geoscience …, 2021 - Elsevier
In this study, we developed multiple hybrid machine-learning models to address parameter
optimization limitations and enhance the spatial prediction of landslide susceptibility models …

Comparison of LiDAR-and UAV-derived data for landslide susceptibility mapping using Random Forest algorithm

F França Pereira, T Sussel Gonçalves Mendes… - Landslides, 2023 - Springer
Earthquakes, extreme rainfall, or human activity can all cause landslides. Several landslides
occur each year around the world, often resulting in casualties and economic …

A comparison among fuzzy multi-criteria decision making, bivariate, multivariate and machine learning models in landslide susceptibility mapping

QB Pham, Y Achour, SA Ali, F Parvin… - … , Natural Hazards and …, 2021 - Taylor & Francis
Landslides are dangerous events which threaten both human life and property. The study
aims to analyze the landslide susceptibility (LS) in the Kysuca river basin, Slovakia. For this …

HR-GLDD: a globally distributed dataset using generalized deep learning (DL) for rapid landslide mapping on high-resolution (HR) satellite imagery

SR Meena, L Nava, K Bhuyan, S Puliero… - Earth System …, 2023 - essd.copernicus.org
Multiple landslide events occur often across the world which have the potential to cause
significant harm to both human life and property. Although a substantial amount of research …

An ensemble random forest tree with SVM, ANN, NBT, and LMT for landslide susceptibility mapping in the Rangit River watershed, India

SA Ali, F Parvin, QB Pham, KM Khedher, M Dehbozorgi… - Natural Hazards, 2022 - Springer
This study examined landslide susceptibility, an increasingly common problem in
mountainous regions across the world as a result of urbanization, deforestation, and various …

[HTML][HTML] GIS-based and Naïve Bayes for nitrogen soil mapping in Lendah, Indonesia

A Yudhana, D Sulistyo, I Mufandi - Sensing and Bio-Sensing Research, 2021 - Elsevier
Rice or Oryza sativa L. is the staple food of Indonesian society. Currently, the demand for
rice in Indonesia is increasing, while the level of rice production is decreasing. Therefore …

Novel ensemble of deep learning neural network and support vector machine for landslide susceptibility mapping in Tehri region, Garhwal Himalaya

S Saha, A Saha, TK Hembram, B Kundu… - Geocarto …, 2022 - Taylor & Francis
Over the years, landslide has become one of the most destructive events that can happen in
hilly areas. Tehri, a region in the Himalayas is no different. Current research aids in the …