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 …
Application of novel data-mining technique based nitrate concentration susceptibility prediction approach for coastal aquifers in India
In water resource management and pollution control research, prediction of nitrate
concentration in groundwater gets utmost priority in the last few years. Thus, our current …
concentration in groundwater gets utmost priority in the last few years. Thus, our current …
Performance of machine learning methods in predicting water quality index based on irregular data set: application on Illizi region (Algerian southeast)
Groundwater quality appraisal is one of the most crucial tasks to ensure safe drinking water
sources. Concurrently, a water quality index (WQI) requires some water quality parameters …
sources. Concurrently, a water quality index (WQI) requires some water quality parameters …
Groundwater level prediction using machine learning algorithms in a drought-prone area
Groundwater resources (GWR) play a crucial role in agricultural crop production, daily life,
and economic progress. Therefore, accurate prediction of groundwater (GW) level will aid in …
and economic progress. Therefore, accurate prediction of groundwater (GW) level will aid in …
[HTML][HTML] Ensemble learning framework for landslide susceptibility mapping: Different basic classifier and ensemble strategy
The application of ensemble learning models has been continuously improved in recent
landslide susceptibility research, but most studies have no unified ensemble framework …
landslide susceptibility research, but most studies have no unified ensemble framework …
A novel hybrid of meta-optimization approach for flash flood-susceptibility assessment in a monsoon-dominated watershed, Eastern India
The exponential growth in the number of flash flood events is a global threat, and detecting a
flood-prone area has also become a top priority. The flash flood-susceptibility mapping can …
flood-prone area has also become a top priority. The flash flood-susceptibility mapping can …
[HTML][HTML] Flood susceptibility mapping using multi-temporal SAR imagery and novel integration of nature-inspired algorithms into support vector regression
Flood has long been known as one of the most catastrophic natural hazards worldwide.
Mapping flood-prone areas is an important part of flood disaster management. In this study …
Mapping flood-prone areas is an important part of flood disaster management. In this study …
[HTML][HTML] DEM resolution effects on machine learning performance for flood probability mapping
Floods are among the devastating natural disasters that occurred very frequently in arid
regions during the last decades. Accurate assessment of the flood susceptibility mapping is …
regions during the last decades. Accurate assessment of the flood susceptibility mapping is …
[HTML][HTML] Flooding and its relationship with land cover change, population growth, and road density
Bangladesh experiences frequent hydro-climatic disasters such as flooding. These disasters
are believed to be associated with land use changes and climate variability. However …
are believed to be associated with land use changes and climate variability. However …
[HTML][HTML] Modeling fragmentation probability of land-use and land-cover using the bagging, random forest and random subspace in the Teesta River Basin …
S Talukdar, KU Eibek, S Akhter, SK Ziaul… - Ecological …, 2021 - Elsevier
Land-use and land-cover (LULC) changes have become a crucial issue that urgently needs
to be addressed due to global environmental change. Many studies have employed remote …
to be addressed due to global environmental change. Many studies have employed remote …