Combining data-intelligent algorithms for the assessment and predictive modeling of groundwater resources quality in parts of southeastern Nigeria

JC Egbueri, JC Agbasi - Environmental Science and Pollution Research, 2022 - Springer
Abstract Machine learning algorithms have proven useful in the estimation, classification,
and prediction of water quality parameters. Similarly, indexical modeling has enhanced the …

Influence of hydro-geochemical processes on groundwater quality through geostatistical techniques in Kadava River basin, Western India

VM Wagh, DB Panaskar, JA Jacobs, SV Mukate… - Arabian Journal of …, 2019 - Springer
Hydrogeochemistry and groundwater quality of the Kadava River Basin have been
performed by analyzing 40 groundwater samples for pre-and post-monsoon seasons of …

Evaluation and prediction of irrigation water quality of an agricultural district, SE Nigeria: an integrated heuristic GIS-based and machine learning approach

ME Omeka - Environmental Science and Pollution Research, 2024 - Springer
Poor irrigation water quality can mar agricultural productivity. Traditional assessment of
irrigation water quality usually requires the computation of various conventional quality …

Seasonal variation in groundwater quality and beneficial use for drinking, irrigation, and industrial purposes from Deccan Basaltic Region, Western India

A Kadam, V Wagh, S Patil, B Umrikar… - … Science and Pollution …, 2021 - Springer
Sustainable management of groundwater resources requires detailed basin-wide water
assessments. Semi-urbanized areas surrounding metropolitan cities in the western part of …

Prediction of potentially toxic elements in water resources using MLP-NN, RBF-NN, and ANFIS: a comprehensive review

JC Agbasi, JC Egbueri - Environmental Science and Pollution Research, 2024 - Springer
Water resources are constantly threatened by pollution of potentially toxic elements (PTEs).
In efforts to monitor and mitigate PTEs pollution in water resources, machine learning (ML) …

Prediction modeling of potentially toxic elements' hydrogeopollution using an integrated Q-mode HCs and ANNs machine learning approach in SE Nigeria

JC Egbueri - Environmental Science and Pollution Research, 2021 - Springer
Abstract Machine learning techniques have proven to be very useful in environmental and
engineering assessments, including water quality studies. This is because they have flexible …

Analysis of different combinations of meteorological parameters and well characteristics in predicting the groundwater chloride concentration with different empirical …

Y Kassem - Environmental Earth Sciences, 2023 - Springer
The main aim of the present study was to select a better model for predicting the
groundwater salinity in the Gaza Strip, Palestine for the first time. The purpose of this work …

Development of AI-based hybrid soft computing models for prediction of critical river water quality indicators

S Gupta, SK Gupta - Environmental Science and Pollution Research, 2024 - Springer
Prediction of river water quality indicators (RWQIs) using artificial intelligence (AI)–based
hybrid soft computing modeling techniques could provide essential predictions required for …

Identifying most influencing input parameters for predicting chloride concentration in groundwater using an ANN approach

Y Kassem, H Gökçekuş, MRM Maliha - Environmental Earth Sciences, 2021 - Springer
Assessment of groundwater quality at a specific location is an important step to provide
adequate information about water management and sustainable development. Several …

Constrained optimization model of the volume of initial rainwater storage tank based on ANN and PSO

S He, W Chen, X Mu, W Cui - Environmental Science and Pollution …, 2020 - Springer
Rainfall runoff pollution is one of the main causes of water quality deterioration in urban
water system. Setting up initial rainwater storage tank could be one of the rapid and effective …