Application of machine learning in groundwater quality modeling-A comprehensive review

R Haggerty, J Sun, H Yu, Y Li - Water Research, 2023 - Elsevier
Groundwater is a crucial resource across agricultural, civil, and industrial sectors. The
prediction of groundwater pollution due to various chemical components is vital for planning …

A review of the artificial neural network models for water quality prediction

Y Chen, L Song, Y Liu, L Yang, D Li - Applied Sciences, 2020 - mdpi.com
Water quality prediction plays an important role in environmental monitoring, ecosystem
sustainability, and aquaculture. Traditional prediction methods cannot capture the nonlinear …

Predictive modeling of groundwater nitrate pollution using Random Forest and multisource variables related to intrinsic and specific vulnerability: A case study in an …

V Rodriguez-Galiano, MP Mendes… - Science of the Total …, 2014 - Elsevier
Watershed management decisions need robust methods, which allow an accurate predictive
modeling of pollutant occurrences. Random Forest (RF) is a powerful machine learning data …

A study of assessment and prediction of water quality index using fuzzy logic and ANN models

R Trach, Y Trach, A Kiersnowska, A Markiewicz… - Sustainability, 2022 - mdpi.com
Various human activities have been the main causes of surface water pollution. The uneven
distribution of industrial enterprises in the territories of the main river basins of Ukraine do …

Groundwater level simulation using soft computing methods with emphasis on major meteorological components

S Samani, M Vadiati, F Azizi, E Zamani… - Water Resources …, 2022 - Springer
Precise estimation of groundwater level (GWL) might be of great importance for attaining
sustainable development goals and integrated water resources management. Compared …

Intelligent soft computational models integrated for the prediction of potentially toxic elements and groundwater quality indicators: a case study

JC Agbasi, JC Egbueri - Journal of sedimentary environments, 2023 - Springer
Reports have shown that potentially toxic elements (PTEs) in air, water, and soil systems
expose humans to carcinogenic and non-carcinogenic health risks. In southeastern Nigeria …

Artificial neural network modeling approach for the prediction of five-day biological oxygen demand and wastewater treatment plant performance

A Alsulaili, A Refaie - Water Supply, 2021 - iwaponline.com
The measurement of the wastewater BOD5 level requires five days, and the use of a
prediction model to estimate BOD5 saves time and enables the adoption of an online control …

Artificial neural network approach for predicting reverse osmosis desalination plants performance in the Gaza Strip

AM Aish, HA Zaqoot, SM Abdeljawad - Desalination, 2015 - Elsevier
A rapidly growing technique for producing new water is desalination of seawater and
brackish water. In the Gaza Strip the maximum amount of the drinking water is produced …

Modelling and optimization of fenton process for decolorization of azo dye (DR16) at microreactor using artificial neural network and genetic algorithm

JS Ahari, M Sadeghi, MK Salooki, M Esfandyari… - Heliyon, 2024 - cell.com
The Fenton process is widely employed for decolorizing industrial wastewater. Therefore, it
is imperative to construct a model for optimizing the operational parameters and estimating …

Application of soft computing models for simulating nitrate contamination in groundwater: comprehensive review, assessment and future opportunities

M Haghbin, A Sharafati, B Dixon, V Kumar - Archives of computational …, 2021 - Springer
Groundwater is one of the major resources to supply the agriculture and urban water
demand. Vulnerability of groundwater resources due to chemical substances is a crucial …