[HTML][HTML] Flood susceptibility modelling using advanced ensemble machine learning models
Floods are one of nature's most destructive disasters because of the immense damage to
land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to …
land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to …
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. Mapping of landslide
susceptibility is an important tool to prevent and control landslide disasters. The purpose of …
susceptibility is an important tool to prevent and control landslide disasters. The purpose of …
Soft computing ensemble models based on logistic regression for groundwater potential mapping
Groundwater potential maps are one of the most important tools for the management of
groundwater storage resources. In this study, we proposed four ensemble soft computing …
groundwater storage resources. In this study, we proposed four ensemble soft computing …
Coupling RBF neural network with ensemble learning techniques for landslide susceptibility mapping
Using multiple ensemble learning techniques for improving the predictive accuracy of
landslide models is an active research area. In this study, we combined a radial basis …
landslide models is an active research area. In this study, we combined a radial basis …
Using analytical hierarchy process and multi-influencing factors to map groundwater recharge zones in a semi-arid Mediterranean coastal aquifer
Mapping groundwater recharge zones (GWRZs) is essential for planning artificial recharge
programs to mitigate groundwater decline and saltwater intrusion into coastal aquifers. We …
programs to mitigate groundwater decline and saltwater intrusion into coastal aquifers. We …
Groundwater potential mapping combining artificial neural network and real AdaBoost ensemble technique: the DakNong province case-study, Vietnam
The main aim of this study is to assess groundwater potential of the DakNong province,
Vietnam, using an advanced ensemble machine learning model (RABANN) that integrates …
Vietnam, using an advanced ensemble machine learning model (RABANN) that integrates …
Ensemble modeling of landslide susceptibility using random subspace learner and different decision tree classifiers
In this study, we have developed five spatially explicit ensemble predictive machine learning
models for the landslide susceptibility mapping of the Van Chan district of the Yen Bai …
models for the landslide susceptibility mapping of the Van Chan district of the Yen Bai …
Landslide and wildfire susceptibility assessment in Southeast Asia using ensemble machine learning methods
Q He, Z Jiang, M Wang, K Liu - Remote Sensing, 2021 - mdpi.com
Southeast Asia (SEA) is a region affected by landslide and wildfire; however, few studies on
susceptibility modeling for the two hazards together have been conducted for this region …
susceptibility modeling for the two hazards together have been conducted for this region …
An ensemble random forest tree with SVM, ANN, NBT, and LMT for landslide susceptibility mapping in the Rangit River watershed, India
This study examined landslide susceptibility, an increasingly common problem in
mountainous regions across the world as a result of urbanization, deforestation, and various …
mountainous regions across the world as a result of urbanization, deforestation, and various …
Improving GALDIT-based groundwater vulnerability predictive mapping using coupled resampling algorithms and machine learning models
Developing accurate groundwater vulnerability maps is important for the sustainable
management of groundwater resources. In this research, resampling methods [eg, Bootstrap …
management of groundwater resources. In this research, resampling methods [eg, Bootstrap …