Indexical and artificial neural network modeling of the quality, corrosiveness, and encrustation potential of groundwater in industrialized metropolises, Southeast Nigeria-Reference-Cited by-同舟云学术

Indexical and artificial neural network modeling of the quality, corrosiveness, and encrustation potential of groundwater in industrialized metropolises, Southeast Nigeria

Published:2022-10-03 Issue: Volume: Page:
ISSN:1387-585X
Container-title:Environment, Development and Sustainability
language:en
Short-container-title:Environ Dev Sustain

Author:

Egbueri Johnbosco C.^ORCID,Unigwe Chinanu O.^ORCID,Agbasi Johnson C.^ORCID,Nwazelibe Vincent E.^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Management, Monitoring, Policy and Law,Economics and Econometrics,Geography, Planning and Development

Link

https://link.springer.com/content/pdf/10.1007/s10668-022-02687-8.pdf

Reference88 articles.

1. Abba, S. I., Pham, Q. B., Saini, G., Linh, N. T. T., Ahmed, A. N., Mohajane, M., Khaledian, M., Abdulkadir, R. A., & Bach, Q.-V. (2020). Implementation of data intelligence models coupled with ensemble machine learning for prediction of water quality index. Environmental Science and Pollution Research, 27, 41524–41539.

2. Abbasnia, A., Yousefi, N., Mahvi, A. H., Nabizadeh, R., Radfard, M., Yousefi, M., et al. (2018). Evaluation of groundwater quality using water quality index and its suitability for assessing water for drinking and irrigation purposes: Case study of Sistan and Baluchistan province (Iran). Human and Ecological Risk Assessment: An International Journal. https://doi.org/10.1080/10807039.2018.1458596

3. Agatemor, C., & Okolo, P. O. (2008). Studies of corrosion tendency of drinking water in the distribution system at the University of Benin. The Environmentalist, 28(4), 379–384. https://doi.org/10.1007/s10669-007-9152-2

4. Agbasi, J. C., & Egbueri, J. C. (2022). Assessment of PTEs in water resources by integrating HHRISK code, water quality indices, multivariate statistics, and ANNs. Geocarto International. https://doi.org/10.1080/10106049.2022.2034990

5. Aghazadeh, N., Chitsazan, M., & Golestan, Y. (2017). Hydrochemistry and quality assessment of groundwater in the Ardabil area, Iran. Applied Water Science, 7, 3599–3616. https://doi.org/10.1007/s13201-016-0498-9

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