Ensemble machine learning paradigms in hydrology: A review
Recently, there has been a notable tendency towards employing ensemble learning
methodologies in assorted areas of engineering, such as hydrology, for simulation and …
methodologies in assorted areas of engineering, such as hydrology, for simulation and …
Flood hazards susceptibility mapping using statistical, fuzzy logic, and MCDM methods
H Akay - Soft Computing, 2021 - Springer
In this study, the flood hazards susceptibility map of an area in Turkey which is frequently
exposed to flooding was predicted by training 70% of inventory data. For this, statistical, and …
exposed to flooding was predicted by training 70% of inventory data. For this, statistical, and …
GIS-based ensemble computational models for flood susceptibility prediction in the Quang Binh Province, Vietnam
Recently, floods are occurring more frequently every year around the world due to increased
anthropogenic activities and climate change. There is a need to develop accurate models for …
anthropogenic activities and climate change. There is a need to develop accurate models for …
Novel ensemble forecasting of streamflow using locally weighted learning algorithm
The development of advanced computational models for improving the accuracy of
streamflow forecasting could save time and cost for sustainable water resource …
streamflow forecasting could save time and cost for sustainable water resource …
Quadratic discriminant analysis based ensemble machine learning models for groundwater potential modeling and mapping
DH Ha, PT Nguyen, R Costache, N Al-Ansari… - Water Resources …, 2021 - Springer
In this study, the AdaBoost, MultiBoost and RealAdaBoost methods were combined with the
Quadratic Discriminant Analysis method to develop three new GIS-based Machine Learning …
Quadratic Discriminant Analysis method to develop three new GIS-based Machine Learning …
Landslide susceptibility mapping using single machine learning models: a case study from Pithoragarh District, India
Landslides are one of the most devastating natural hazards causing huge loss of life and
damage to properties and infrastructures and adversely affecting the socioeconomy of the …
damage to properties and infrastructures and adversely affecting the socioeconomy of the …
[HTML][HTML] APG: A novel python-based ArcGIS toolbox to generate absence-datasets for geospatial studies
One important step in binary modeling of environmental problems is the generation of
absence-datasets that are traditionally generated by random sampling and can undermine …
absence-datasets that are traditionally generated by random sampling and can undermine …
Construction and application of reservoir flood control operation rules using the decision tree algorithm
Y Diao, C Wang, H Wang, Y Liu - Water, 2021 - mdpi.com
Current conventional and optimal reservoir flood control operation methods insufficiently
utilize historical reservoir operation data, which include rainfall, runoff generation, and inflow …
utilize historical reservoir operation data, which include rainfall, runoff generation, and inflow …
Enhancing flood prediction using ensemble and deep learning techniques
Though flooding is seen as a common environmental threat globally, it has dramatically
increased recently due to climate change, impacting underdeveloped and developing …
increased recently due to climate change, impacting underdeveloped and developing …
[PDF][PDF] Research Article Landslide Susceptibility Mapping Using Single Machine Learning Models: A Case Study from Pithoragarh District, India
Landslides are one of the most devastating natural hazards causing huge loss of life and
damage to properties and infrastructures and adversely affecting the socioeconomy of the …
damage to properties and infrastructures and adversely affecting the socioeconomy of the …