Prediction of Moisture Content Removal from Sludge by Artificial Neural Network Modelling

Zhi Fu, Joidan Lau (2020) Prediction of Moisture Content Removal from Sludge by Artificial Neural Network Modelling. [Final Year Project] (Submitted)

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Abstract

This study predicted the moisture content removed from sludge samples which underwent oven-dry tests by means of neural artificial network modelling. Sludge management is a global predicament in which challenges in solving it include cost- saving, space usage-optimization, and environmentalism. Information pertaining to drying sludge and removing its moisture content is pertinent as it determines sludge management quality as it determines the costs of management. Hence, a model predicting sludge moisture content could help provide more insight into dewatering sludge which is often overlooked, in contrast to techniques of dewatering sludge. There remains a dearth of research done in this regard. Hence this endeavor is worthwhile for the potential expansions of such work may make headway to more profitable discoveries.

Item Type: Final Year Project
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Departments / MOR / COE: Engineering > Civil
Depositing User: Mr Ahmad Suhairi Mohamed Lazim
Date Deposited: 14 Sep 2021 08:30
Last Modified: 14 Sep 2021 08:30
URI: http://utpedia.utp.edu.my/id/eprint/21048

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