A survey on river water quality modelling using artificial intelligence models: 2000–2020
There has been an unsettling rise in the river contamination due to the climate change and
anthropogenic activities. Last decades' research has immensely focussed on river basin …
anthropogenic activities. Last decades' research has immensely focussed on river basin …
Groundwater availability and water demand sustainability over the upper mega aquifers of Arabian Peninsula and west region of Iraq
The current research is devoted to highlight the past, present and future status of
groundwater characteristics over the Arabian Peninsula (AP) and west region of Iraq. The …
groundwater characteristics over the Arabian Peninsula (AP) and west region of Iraq. The …
Modeling pan evaporation using Gaussian process regression K-nearest neighbors random forest and support vector machines; comparative analysis
Evaporation is a very important process; it is one of the most critical factors in agricultural,
hydrological, and meteorological studies. Due to the interactions of multiple climatic factors …
hydrological, and meteorological studies. Due to the interactions of multiple climatic factors …
Optimized ANFIS model using hybrid metaheuristic algorithms for Parkinson's disease prediction in IoT environment
Throughout recent years, the progress of telemonitoring and telediagnostics devices for
evaluating and tracking Parkinson's (PD) disease has become increasingly important. The …
evaluating and tracking Parkinson's (PD) disease has become increasingly important. The …
A survey towards decision support system on smart irrigation scheduling using machine learning approaches
From last decade, Big data analytics and machine learning is a hotspot research area in the
domain of agriculture. Agriculture analytics is a data intensive multidisciplinary problem. Big …
domain of agriculture. Agriculture analytics is a data intensive multidisciplinary problem. Big …
Deep learning versus gradient boosting machine for pan evaporation prediction
In the present study, two innovative techniques namely, Deep Learning (DL) and Gradient
boosting Machine (GBM) models are developed based on a maximum air temperature …
boosting Machine (GBM) models are developed based on a maximum air temperature …
[PDF][PDF] A novel framework for selecting general circulation models based on the spatial patterns of climate
MS Nashwan, S Shahid - International Journal of Climatology, 2020 - researchgate.net
General circulation models (GCMs), used for climate change projections, should be able to
simulate both the temporal variability and spatial patterns of the observed climate. However …
simulate both the temporal variability and spatial patterns of the observed climate. However …
A systematic literature review on lake water level prediction models
Global climate change has led to large fluctuations in lake levels in recent years as
meteorological and hydrological parameters have changed and water use has been …
meteorological and hydrological parameters have changed and water use has been …
Modeling climate change impact on wind power resources using adaptive neuro-fuzzy inference system
Climate change impacts and adaptations are ongoing issues that are attracting the attention
of many researchers. Insight into the wind power potential in an area and its probable …
of many researchers. Insight into the wind power potential in an area and its probable …
On the complexities of sediment load modeling using integrative machine learning: Application of the great river of Loíza in Puerto Rico
M Zounemat-Kermani, A Mahdavi-Meymand… - Journal of …, 2020 - Elsevier
Sediment transportation in water bodies may cause many problems for the water resources
projects and damage the environment. Hence, modeling sediment load components …
projects and damage the environment. Hence, modeling sediment load components …