Advancing SDGs: Predicting Future Shifts in Saudi Arabia's Terrestrial Water Storage Using Multi-Step-Ahead Machine Learning Based on GRACE Data
The availability of water is crucial for the growth and sustainability of human development.
The effective management of water resources is essential due to their renewable nature and …
The effective management of water resources is essential due to their renewable nature and …
Prediction of aeration efficiency of parshall and modified venturi flumes: application of soft computing versus regression models
In this study, the potential of soft computing techniques, namely Random Forest (RF), M5P,
Multivariate Adaptive Regression Splines (MARS), and Group Method of Data Handling …
Multivariate Adaptive Regression Splines (MARS), and Group Method of Data Handling …
Parameter estimation and assessment of infiltration models for Madjez Ressoul Catchment, Algeria
Evaluation and modeling of soil water infiltration are essential to all aspects of water
resources management and the design of hydraulic structures. Nonetheless, research …
resources management and the design of hydraulic structures. Nonetheless, research …
Daily scale air quality index forecasting using bidirectional recurrent neural networks: Case study of Delhi, India
This research was established to accurately forecast daily scale air quality index (AQI) which
is an essential environmental index for decision-making. Researchers have projected …
is an essential environmental index for decision-making. Researchers have projected …
[HTML][HTML] Comparative analysis of machine learning algorithms for water quality prediction
This study aims to identify the influential parameters and heavy metals in water and assess
the water quality classification at the Alpine glacial lakes and rivers in three districts of …
the water quality classification at the Alpine glacial lakes and rivers in three districts of …
Rainfall modeling using two different neural networks improved by metaheuristic algorithms
Rainfall is crucial for the development and management of water resources. Six hybrid soft
computing models, including multilayer perceptron (MLP)–Henry gas solubility optimization …
computing models, including multilayer perceptron (MLP)–Henry gas solubility optimization …
Predictive modelling of nitrogen dioxide using soft computing techniques in the Agra, Uttar Pradesh, India
Nitrogen dioxide (NO 2) is one of the air pollutants which aggravates the human health as
well as causes environmental issues. It is more causes respiratory problems due to acid …
well as causes environmental issues. It is more causes respiratory problems due to acid …
Developing an ensembled machine learning model for predicting water quality index in Johor River Basin
Abstract Currently, the Water Quality Index (WQI) model becomes a widely used tool to
evaluate surface water quality for agriculture, domestic and industrial. WQI is one of the …
evaluate surface water quality for agriculture, domestic and industrial. WQI is one of the …
Estimation of Reference Evapotranspiration in Semi-Arid Region with Limited Climatic Inputs Using Metaheuristic Regression Methods
Different regression-based machine learning techniques, including support vector machine
(SVM), random forest (RF), Bagged trees algorithm (BaT), and Boosting trees algorithm …
(SVM), random forest (RF), Bagged trees algorithm (BaT), and Boosting trees algorithm …
Estimating the permeability coefficient of soil using CART and GMDH approaches
M Torabi, H Sarkardeh, SM Mirhosseini - Water Supply, 2022 - iwaponline.com
Permeability coefficient of soil (k) is one of the most important parameters in groundwater
studies. This study, two robust explicit data-driven methods, Including classification and …
studies. This study, two robust explicit data-driven methods, Including classification and …