Incorporation of information entropy theory, artificial neural network, and soft computing models in the development of integrated industrial water quality index
Author:
Publisher
Springer Science and Business Media LLC
Subject
Management, Monitoring, Policy and Law,Pollution,General Environmental Science,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s10661-022-10389-x.pdf
Reference81 articles.
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3. 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. https://doi.org/10.1080/10807039.2018.1458596
4. Abyaneh, H. Z., Varkeshi, M. B., Mohammadi, K., Howard, K., & Marofi, S. (2011). Assessment of groundwater corrosivity in Hamedan Province, Iran using an adaptive neuro-fuzzy inference system (ANFIS). Geosciences Journal, 15(4), 433–439. https://doi.org/10.1007/s12303-011-0032-x
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