Modeling surface water quality using the adaptive neuro-fuzzy inference system aided by input optimization
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Shah, Muhammad Izhar 
ORCID: 0000-0002-0588-6301, Abunama, Taher ORCID: 0000-0002-8588-898X, Javed, Muhammad Faisal ORCID: 0000-0001-5478-9324, Bux, Faizal ORCID: 0000-0002-8108-0238, Aldrees, Ali ORCID: 0000-0001-6575-6181, Tariq, Muhammad Atiq Ur Rehman ORCID: 0000-0002-0226-7310 and Mosavi, Amir ORCID: 0000-0003-4842-0613
(2021)
Modeling surface water quality using the adaptive neuro-fuzzy inference system aided by input optimization.
Sustainability (Switzerland), 13 (8).
ISSN 2071-1050
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| Item type | Article |
| URI | https://vuir.vu.edu.au/id/eprint/44524 |
| DOI | 10.3390/su13084576 |
| Official URL | https://www.mdpi.com/2071-1050/13/8/4576 |
| Subjects | Current > FOR (2020) Classification > 4005 Civil engineering Current > Division/Research > College of Science and Engineering Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
| Keywords | soft computing techniques, environmental protection, predictive models, Artificial intelligence, Big data, Hydrology, Input optimiza-tion, Machine learning, neuro-fuzzy, Outlier detection, Surface water quality, Water quality management |
| Citations in Scopus | 24 - View on Scopus |
| Download/View statistics | View download statistics for this item |
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