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Flood susceptibility map** with machine learning, multi-criteria decision analysis and ensemble using Dempster Shafer Theory
Floods are one of the most widespread natural hazards occurring across the globe. The
main objective of this study was to produce flood susceptibility maps for the province of …
main objective of this study was to produce flood susceptibility maps for the province of …
[HTML][HTML] State of the art and recent advancements in the modelling of land subsidence induced by groundwater withdrawal
Land subsidence is probably one of the most evident environmental effects of groundwater
pum**. Globally, freshwater demand is the leading cause of this phenomenon. Land …
pum**. Globally, freshwater demand is the leading cause of this phenomenon. Land …
Evaluation of different machine learning methods and deep-learning convolutional neural networks for landslide detection
There is a growing demand for detailed and accurate landslide maps and inventories
around the globe, but particularly in hazard-prone regions such as the Himalayas. Most …
around the globe, but particularly in hazard-prone regions such as the Himalayas. Most …
[HTML][HTML] Evaluation of deep learning algorithms for national scale landslide susceptibility map** of Iran
The identification of landslide-prone areas is an essential step in landslide hazard
assessment and mitigation of landslide-related losses. In this study, we applied two novel …
assessment and mitigation of landslide-related losses. In this study, we applied two novel …
[HTML][HTML] Forest fire susceptibility and risk map** using social/infrastructural vulnerability and environmental variables
Forests fires in northern Iran have always been common, but the number of forest fires has
been growing over the last decade. It is believed, but not proven, that this growth can be …
been growing over the last decade. It is believed, but not proven, that this growth can be …
[HTML][HTML] Deep learning and machine learning models for landslide susceptibility map** with remote sensing data
Karakoram Highway (KKH) is an international route connecting South Asia with Central Asia
and China that holds socio-economic and strategic significance. However, KKH has extreme …
and China that holds socio-economic and strategic significance. However, KKH has extreme …
Development of artificial intelligence models for the prediction of Compression Coefficient of soil: An application of Monte Carlo sensitivity analysis
In this study, we developed Different Artificial Intelligence (AI) models namely Artificial
Neural Network (ANN), Adaptive Network based Fuzzy Inference System (ANFIS) and …
Neural Network (ANN), Adaptive Network based Fuzzy Inference System (ANFIS) and …
[HTML][HTML] Comparisons of diverse machine learning approaches for wildfire susceptibility map**
K Gholamnia, T Gudiyangada Nachappa… - Symmetry, 2020 - mdpi.com
Climate change has increased the probability of the occurrence of catastrophes like
wildfires, floods, and storms across the globe in recent years. Weather conditions continue to …
wildfires, floods, and storms across the globe in recent years. Weather conditions continue to …
[HTML][HTML] Optimization of computational intelligence models for landslide susceptibility evaluation
X Zhao, W Chen - Remote Sensing, 2020 - mdpi.com
This paper focuses on landslide susceptibility prediction in Nanchuan, a high-risk landslide
disaster area. The evidential belief function (EBF)-based function tree (FT), logistic …
disaster area. The evidential belief function (EBF)-based function tree (FT), logistic …
[HTML][HTML] Spatial prediction of wildfire susceptibility using field survey GPS data and machine learning approaches
Recently, global climate change discussions have become more prominent, and forests are
considered as the ecosystems most at risk by the consequences of climate change. Wildfires …
considered as the ecosystems most at risk by the consequences of climate change. Wildfires …