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 …

Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance

A Merghadi, AP Yunus, J Dou, J Whiteley… - Earth-Science …, 2020 - Elsevier
Landslides are one of the catastrophic natural hazards that occur in mountainous areas,
leading to loss of life, damage to properties, and economic disruption. Landslide …

Applications of artificial intelligence for disaster management

W Sun, P Bocchini, BD Davison - Natural Hazards, 2020 - Springer
Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …

Improved landslide assessment using support vector machine with bagging, boosting, and stacking ensemble machine learning framework in a mountainous …

J Dou, AP Yunus, DT Bui, A Merghadi, M Sahana… - Landslides, 2020 - Springer
Heavy rainfall in mountainous terrain can trigger numerous landslides in hill slopes. These
landslides can be deadly to the community living downslope with their fast pace, turning …

A comparative assessment of flood susceptibility modeling using multi-criteria decision-making analysis and machine learning methods

K Khosravi, H Shahabi, BT Pham, J Adamowski… - Journal of …, 2019 - Elsevier
Floods around the world are having devastating effects on human life and property. In this
paper, three Multi-Criteria Decision-Making (MCDM) analysis techniques (VIKOR, TOPSIS …

Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan

J Dou, AP Yunus, DT Bui, A Merghadi… - Science of the total …, 2019 - Elsevier
Landslides represent a part of the cascade of geological hazards in a wide range of geo-
environments. In this study, we aim to investigate and compare the performance of two state …

A comparative study of PSO-ANN, GA-ANN, ICA-ANN, and ABC-ANN in estimating the heating load of buildings' energy efficiency for smart city planning

LT Le, H Nguyen, J Dou, J Zhou - Applied Sciences, 2019 - mdpi.com
Energy-efficiency is one of the critical issues in smart cities. It is an essential basis for
optimizing smart cities planning. This study proposed four new artificial intelligence (AI) …

GIS-based evaluation of landslide susceptibility using hybrid computational intelligence models

W Chen, Y Li - Catena, 2020 - Elsevier
Landslides have caused huge economic and human losses in China. Map** of landslide
susceptibility is an important tool to prevent and control landslide disasters. The purpose of …

Hybrid integration of Multilayer Perceptron Neural Networks and machine learning ensembles for landslide susceptibility assessment at Himalayan area (India) using …

BT Pham, DT Bui, I Prakash, MB Dholakia - Catena, 2017 - Elsevier
The main objective of this study is to evaluate and compare the performance of landslide
models using machine learning ensemble technique for landslide susceptibility assessment …

Shallow landslide susceptibility map**: A comparison between logistic model tree, logistic regression, naïve bayes tree, artificial neural network, and support vector …

VH Nhu, A Shirzadi, H Shahabi, SK Singh… - International journal of …, 2020 - mdpi.com
Shallow landslides damage buildings and other infrastructure, disrupt agriculture practices,
and can cause social upheaval and loss of life. As a result, many scientists study the …