Fault prediction based on leakage current in contaminated insulators using enhanced time series forecasting models
To improve the monitoring of the electrical power grid, it is necessary to evaluate the
influence of contamination in relation to leakage current and its progression to a disruptive …
influence of contamination in relation to leakage current and its progression to a disruptive …
[HTML][HTML] GIS-based mineral prospectivity mapping using machine learning methods: A case study from Tongling ore district, eastern China
T Sun, F Chen, L Zhong, W Liu, Y Wang - Ore Geology Reviews, 2019 - Elsevier
Predictive modelling of mineral prospectivity using GIS is a valid and progressively more
accepted tool for delineating reproducible mineral exploration targets. In this study, machine …
accepted tool for delineating reproducible mineral exploration targets. In this study, machine …
[HTML][HTML] Application of remote sensing and machine learning algorithms for forest fire mapping in a Mediterranean area
Forest fire disaster is currently the subject of intense research worldwide. The development
of accurate strategies to prevent potential impacts and minimize the occurrence of disastrous …
of accurate strategies to prevent potential impacts and minimize the occurrence of disastrous …
Lung cancer risk prediction with machine learning models
The lungs are the center of breath control and ensure that every cell in the body receives
oxygen. At the same time, they filter the air to prevent the entry of useless substances and …
oxygen. At the same time, they filter the air to prevent the entry of useless substances and …
A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility mapping
This study introduces four heterogeneous ensemble-learning techniques, that is, stacking,
blending, simple averaging, and weighted averaging, to predict landslide susceptibility in …
blending, simple averaging, and weighted averaging, to predict landslide susceptibility in …
Hydrogeochemical evaluation of groundwater aquifers and associated health hazard risk mapping using ensemble data driven model in a water scares plateau region …
D Ruidas, SC Pal, ARM Towfiqul Islam, A Saha - Exposure and Health, 2023 - Springer
Health hazard risk mapping (HHRM) is an important technique used to estimate the potential
health risk of an individual, a group, or an entire community of a region. To further progress …
health risk of an individual, a group, or an entire community of a region. To further progress …
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 …
A novel deep learning neural network approach for predicting flash flood susceptibility: A case study at a high frequency tropical storm area
This research proposes and evaluates a new approach for flash flood susceptibility mapping
based on Deep Learning Neural Network (DLNN)) algorithm, with a case study at a high …
based on Deep Learning Neural Network (DLNN)) algorithm, with a case study at a high …
Flash flood susceptibility modeling using an optimized fuzzy rule based feature selection technique and tree based ensemble methods
The main objective of the present study was to provide a novel methodological approach for
flash flood susceptibility modeling based on a feature selection method (FSM) and tree …
flash flood susceptibility modeling based on a feature selection method (FSM) and tree …
Time series forecasting using ensemble learning methods for emergency prevention in hydroelectric power plants with dam
In hydroelectric plants, the responsibility for the operation of the reservoirs typically lies with
the national system operator, who controls the level of the reservoirs based on a stochastic …
the national system operator, who controls the level of the reservoirs based on a stochastic …