Enhancing riverine load prediction of anthropogenic pollutants: Harnessing the potential of feed-forward backpropagation (FFBP) artificial neural network (ANN) models
Assessing riverine pollutant loads is a more realistic method for analysing point and non-point anthropogenic pollution sources throughout a watershed. This study compares numerous mathematical modelling strategies for estimating riverine loads based on the chosen water quality parameters: Biochemic...
| Published in: | Results in Engineering |
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| Main Author: | |
| Format: | Article |
| Language: | English |
| Published: |
Elsevier B.V.
2024
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189939391&doi=10.1016%2fj.rineng.2024.102072&partnerID=40&md5=1b41e5180e4e2c5be04e5a5ecaa86eed |