Ensemble models based on radial basis function network for landslide susceptibility mapping
N Le Minh, PT Truyen, T Van Phong, A Jaafari… - … Science and Pollution …, 2023 - Springer
Ensemble learning techniques have shown promise in improving the accuracy of landslide
models by combining multiple models to achieve better predictive performance. In this study …
models by combining multiple models to achieve better predictive performance. In this study …
Quantifying soil erosion and influential factors in Guwahati's urban watershed using statistical analysis, machine and deep learning
Soil erosion is a complex environmental issue influenced by rapid climate change, resource
exploitation, and soil degradation etc. These factors have triggered global acceleration of …
exploitation, and soil degradation etc. These factors have triggered global acceleration of …
Assessing landscape ecological vulnerability to riverbank erosion in the Middle Brahmaputra floodplains of Assam, India using machine learning algorithms
Riverbank erosion is one of the most catastrophic hazards that renders floodplains
vulnerable across the world vulnerable. It creates a significant negative impact on the …
vulnerable across the world vulnerable. It creates a significant negative impact on the …
Landslide susceptibility assessment using remote sensing and GIS-a review
V Bhardwaj, K Singh - Journal of Mining and Environment, 2023 - jme.shahroodut.ac.ir
Natural hazards are naturally occurring phenomena that might lead to a negative impact on
the environment and also on the life of living beings. These hazards are caused due to …
the environment and also on the life of living beings. These hazards are caused due to …
Integrated deep learning with explainable artificial intelligence for enhanced landslide management
Landslides pose significant threats to mountainous regions, causing widespread damage to
both property and human lives. This study seeks to enhance landslide prediction in the …
both property and human lives. This study seeks to enhance landslide prediction in the …
Developing robust flood susceptibility model with small numbers of parameters in highly fertile regions of Northwest Bangladesh for sustainable flood and agriculture …
The present study intends to improve the robustness of a flood susceptibility (FS) model with
a small number of parameters in data-scarce areas, such as northwest Bangladesh, by …
a small number of parameters in data-scarce areas, such as northwest Bangladesh, by …
Enhancing landslide management with hyper-tuned machine learning and deep learning models: Predicting susceptibility and analyzing sensitivity and uncertainty
Introduction Natural hazards such as landslides and floods have caused significant damage
to properties, natural resources, and human lives. The increased anthropogenic activities in …
to properties, natural resources, and human lives. The increased anthropogenic activities in …
Improving Landslide Susceptibility Prediction in Uttarakhand through Hyper-Tuned Artificial Intelligence and Global Sensitivity Analysis
Landslides are constantly increasing in the Himalayan region due to strong tectonic
activities, soil erosion, heavy rainfall, and anthropogenic activities. Despite the severe …
activities, soil erosion, heavy rainfall, and anthropogenic activities. Despite the severe …
Analysis of conditioning factors in cuenca, ecuador, for landslide susceptibility maps generation employing machine learning methods
Landslides are events that cause great impact in different parts of the world. Their
destructive capacity generates loss of life and considerable economic damage. In this …
destructive capacity generates loss of life and considerable economic damage. In this …
[HTML][HTML] A novel hybrid model for developing groundwater potentiality model using high resolution digital elevation model (DEM) derived factors
The present work aims to build a unique hybrid model by combining six fuzzy operator
feature selection-based techniques with logistic regression (LR) for producing groundwater …
feature selection-based techniques with logistic regression (LR) for producing groundwater …