Enhancing riverine load prediction of anthropogenic pollutants: Harnessing the potential of feed-forward backpropagation (FFBP) artificial neural network (ANN) models

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...

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Bibliographic Details
Published in:Results in Engineering
Main Author: Khairudin K.; Ul-Saufie A.Z.; Senin S.F.; Zainudin Z.; Rashid A.M.; Abu Bakar N.F.; Anas Abd Wahid M.Z.; Azha S.F.; Abd-Wahab F.; Wang L.; Sahar F.N.; Osman M.S.
Format: Article
Language:English
Published: Elsevier B.V. 2024
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

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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189939391&doi=10.1016%2fj.rineng.2024.102072&partnerID=40&md5=1b41e5180e4e2c5be04e5a5ecaa86eed

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