[HTML][HTML] Ensemble learning models with a Bayesian optimization algorithm for mineral prospectivity map**
J Yin, N Li - Ore geology reviews, 2022 - Elsevier
Abstract Machine learning algorithms have been widely applied in mineral prospectivity
map** (MPM). In this study, we implemented ensemble learning of extreme gradient …
map** (MPM). In this study, we implemented ensemble learning of extreme gradient …
An overview of multi-criteria decision analysis (MCDA) application in managing water-related disaster events: analyzing 20 years of literature for flood and drought …
This paper provides an overview of multi-criteria decision analysis (MCDA) applications in
managing water-related disasters (WRD). Although MCDA has been widely used in …
managing water-related disasters (WRD). Although MCDA has been widely used in …
[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 …
XGBoost-based method for flash flood risk assessment
M Ma, G Zhao, B He, Q Li, H Dong, S Wang, Z Wang - Journal of Hydrology, 2021 - Elsevier
Flash flood risk assessment, a widely applied technology in preventing catastrophic flash
flood disasters, has become the current research hotspot. However, most existing machine …
flood disasters, has become the current research hotspot. However, most existing machine …
[HTML][HTML] DEM resolution effects on machine learning performance for flood probability map**
Floods are among the devastating natural disasters that occurred very frequently in arid
regions during the last decades. Accurate assessment of the flood susceptibility map** is …
regions during the last decades. Accurate assessment of the flood susceptibility map** is …
Evaluating public transport service quality using picture fuzzy analytic hierarchy process and linear assignment model
Group decision-making on a public service problem is often biased by untrustworthy
responses of the participants, which affects negatively the outcome of the procedure. To …
responses of the participants, which affects negatively the outcome of the procedure. To …
[HTML][HTML] A hybrid of ensemble machine learning models with RFE and Boruta wrapper-based algorithms for flash flood susceptibility assessment
Flash floods are among the world most destructive natural disasters, and develo**
optimum hybrid Machine Learning (ML) models for flash flood susceptibility (FFS) modeling …
optimum hybrid Machine Learning (ML) models for flash flood susceptibility (FFS) modeling …
A comparative assessment of flood susceptibility modelling of GIS-based TOPSIS, VIKOR, and EDAS techniques in the Sub-Himalayan foothills region of Eastern India
Abstract In the Sub-Himalayan foothills region of eastern India, floods are considered the
most powerful annually occurring natural disaster, which cause severe losses to the socio …
most powerful annually occurring natural disaster, which cause severe losses to the socio …
A Google Earth Engine approach for wildfire susceptibility prediction fusion with remote sensing data of different spatial resolutions
The effects of the spatial resolution of remote sensing (RS) data on wildfire susceptibility
prediction are not fully understood. In this study, we evaluate the effects of coarse (Landsat 8 …
prediction are not fully understood. In this study, we evaluate the effects of coarse (Landsat 8 …
[HTML][HTML] An XGBoost-SHAP approach to quantifying morphological impact on urban flooding susceptibility
Urban flooding risks, often overlooked by conventional methods, can be profoundly affected
by city configurations. However, explainable Artificial Intelligence could provide insights into …
by city configurations. However, explainable Artificial Intelligence could provide insights into …