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 …

Analysis and evaluation of landslide susceptibility: a review on articles published during 2005–2016 (periods of 2005–2012 and 2013–2016)

HR Pourghasemi, Z Teimoori Yansari… - Arabian Journal of …, 2018 - Springer
Landslides are one of the most important environmental hazards occur naturally or human-
induced with large-scale social, economic, and environmental impacts. Landslide …

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] 基于优化负样本采样策略的梯度提升决策树与随机森林的汶川同震滑坡易发性评价

郭衍昊, 窦杰, 向子林, 马豪, 董傲男, 罗万祺 - 地质科技通报, 2024 - dzkjqb.cug.edu.cn
强震诱发的滑坡具有数量多, 分布广, 规模大等特点, 严重威胁人民生命财产安全.
滑坡易发性评价能够快速预测灾害空间分布, 对于减轻震后灾害的危险性具有重要意义 …

A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility

W Chen, X Xie, J Wang, B Pradhan, H Hong, DT Bui… - Catena, 2017 - Elsevier
The main purpose of the present study is to use three state-of-the-art data mining
techniques, namely, logistic model tree (LMT), random forest (RF), and classification and …

Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)

H Hong, J Liu, DT Bui, B Pradhan, TD Acharya… - Catena, 2018 - Elsevier
Landslides are a manifestation of slope instability causing different kinds of damage
affecting life and property. Therefore, high-performance-based landslide prediction models …

Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression …

B Kalantar, B Pradhan, SA Naghibi… - … , Natural Hazards and …, 2018 - Taylor & Francis
Landslide is a natural hazard that results in many economic damages and human losses
every year. Numerous researchers have studied landslide susceptibility mapping (LSM) …

GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran

SA Naghibi, HR Pourghasemi, B Dixon - Environmental monitoring and …, 2016 - Springer
Groundwater is considered one of the most valuable fresh water resources. The main
objective of this study was to produce groundwater spring potential maps in the Koohrang …

Landslide susceptibility mapping using random forest, boosted regression tree, classification and regression tree, and general linear models and comparison of their …

AM Youssef, HR Pourghasemi, ZS Pourtaghi… - Landslides, 2016 - Springer
The purpose of the current study is to produce landslide susceptibility maps using different
data mining models. Four modeling techniques, namely random forest (RF), boosted …

Landslide spatial modeling: Introducing new ensembles of ANN, MaxEnt, and SVM machine learning techniques

W Chen, HR Pourghasemi, A Kornejady, N Zhang - Geoderma, 2017 - Elsevier
Abstract “Spatial contraindication” is what exactly landslide susceptibility models have been
seeking. They are designed for depicting perilous land activities, be it natural or …