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: Biochemi...

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Bibliographic Details
Published in:RESULTS IN ENGINEERING
Main Authors: Khairudin, Khairunnisa; Ul-Saufie, Ahmad Zia; Senin, Syahrul Fithry; Zainudin, Zaki; Rashid, Ammar Mohd; Bakar, Noor Fitrah Abu; Wahid, Muhammad Zakwan Anas Abd; Azha, Syahida Farhan; Abd-Wahab, Firdaus; Wang, Lei; Sahar, Farisha Nerina; Osman, Mohamed Syazwan
Format: Article
Language:English
Published: ELSEVIER 2024
Subjects:
Engineering
Online Access:https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001228264500001

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