A systematic evaluation of advanced machine learning models for nickel contamination management in soil using spectral data DOI Creative Commons

Kechao Li,

Tao Hu, Min Zhou

et al.

Journal of Hazardous Materials Advances, Journal Year: 2024, Volume and Issue: unknown, P. 100576 - 100576

Published: Dec. 1, 2024

Language: Английский

Metal(loid)s, nitrate, polycyclic aromatic hydrocarbons, and radioactive contaminants in Nigerian water resources: state-of-the-art of their ecological and health risk assessments DOI
Johnbosco C. Egbueri, Johnson C. Agbasi, Arinze Longinus Ezugwu

et al.

Environment Development and Sustainability, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 28, 2024

Language: Английский

Citations

22
Analytical Examination of the Nutritional Status of Drinking Water Resources: A First Case Application in Africa DOI
Johnson C. Agbasi, Johnbosco C. Egbueri, Anwar A. Alghamdi

et al.

Analytical Letters, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 17

Published: Nov. 12, 2024

Water quality assessment is crucial for public and ecosystem health, yet traditional approaches often overlook the nutritional aspects of drinking water. This study introduces Drinking Nutritional Quality Index (DWNQI) to Africa, presenting its first application in continent. The research evaluated status water resources semi-urban areas Southeast Nigeria, shifting from a contaminant-focused paradigm. samples were strategically collected various sources. Five key elements (Na+, Mg2+, Ca2+, Mn2+, Zn2+) that play roles both human health environmental processes considered. DWNQI model revealed concerning trend, with scores ranging 9.76 78.54 (average 32.02). analysis showed 73.33% fell within "Poor" category, 13.33% "Marginal," 6.67% "Fair," "Good" categories, no reaching excellent range, indicating low trend area. Sensitivity reveal Mg2+and Ca2+ exerted most influence on studied samples. Removal Mg2+ index resulted 23.77% decrease average score, while removal led 23.42% decrease. Key recommendations include implementing targeted mineral enrichment programs developing initiatives address potential deficiencies. contributes sustainability by providing new perspective quality, potentially informing management policies guiding interventions African settings beyond.

Language: Английский

Citations

10
A comparative hydrochemical assessment of groundwater quality for drinking and irrigation purposes using different statistical and ML models in lower gangetic alluvial plain, eastern India DOI

Sribas Kanji,

Subhasish Das,

Chandi Rajak

et al.

Chemosphere, Journal Year: 2025, Volume and Issue: 372, P. 144074 - 144074

Published: Jan. 13, 2025

Language: Английский

Citations

1
Integrating machine learning models for optimizing ecosystem health assessments through prediction of nitrate–N concentrations in the lower stretch of Ganga River, India DOI
Basanta Kumar Das,

Soumitra Paul,

Biswajit Mandal

et al.

Environmental Science and Pollution Research, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 30, 2025

Language: Английский

Citations

1
Groundwater Salinization in Coastal Regions and the Control Mechanisms: Insights for Sustainable Groundwater Development and Management DOI
Johnson C. Agbasi, Mahamuda Abu,

Chaitanya B. Pande

et al.

Springer hydrogeology, Journal Year: 2025, Volume and Issue: unknown, P. 165 - 191

Published: Jan. 1, 2025

Language: Английский

Citations

1
An Innovative Combination of Extra Trees within AdaBoost for Accurate Prediction of Agricultural Water Quality Indices DOI Creative Commons
Mahmood Yousefi, Vahide Oskoei,

H Esmaeli

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: 24, P. 103534 - 103534

Published: Nov. 24, 2024

Language: Английский

Citations

6
Groundwater quality assessment using machine learning models: a comprehensive study on the industrial corridor of a semi-arid region DOI

Loganathan Krishnamoorthy,

V. Lakshmanan

Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: unknown

Published: July 4, 2024

Language: Английский

Citations

4
Optimizing coastal groundwater quality predictions: A novel data mining framework with cross-validation, bootstrapping, and entropy analysis DOI
Abu Reza Md. Towfiqul Islam, Md. Abdullah-Al Mamun, Mehedi Hasan

et al.

Journal of Contaminant Hydrology, Journal Year: 2024, Volume and Issue: 269, P. 104480 - 104480

Published: Dec. 10, 2024

Language: Английский

Citations

4
Forecasting biochemical oxygen demand (BOD) in River Ganga: a case study employing supervised machine learning and ANN techniques DOI
Rohan Mishra,

Rupanjali Singh,

C. B. Majumder

et al.

Sustainable Water Resources Management, Journal Year: 2025, Volume and Issue: 11(1)

Published: Jan. 16, 2025

Language: Английский

Citations

0
Orbital prediction accuracy improvement method based on particle swarm optimization RBF neural network DOI
Mengyao Guo, Tien‐Fu Lu,

S.X. Chen

et al.

Advances in Space Research, Journal Year: 2025, Volume and Issue: unknown

Published: March 1, 2025

Language: Английский

Citations

0