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Prediction analysis of effluent removal in a septic sludge treatment plant: A biomimetics engineering approach

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dc.citedby2
dc.contributor.authorChun T.S.en_US
dc.contributor.authorMalek M.A.en_US
dc.contributor.authorIsmail A.R.en_US
dc.contributor.authorid56338030500en_US
dc.contributor.authorid55636320055en_US
dc.contributor.authorid36995749000en_US
dc.date.accessioned2023-05-16T02:47:00Z
dc.date.available2023-05-16T02:47:00Z
dc.date.issued2014
dc.description.abstractEffluent discharge from septic tanks is affecting the environment in developing countries. The most challenging issue facing these countries is the cost of inadequate sanitation, which includes significant economic, social, and environmental burdens. Although most sanitation facilities are evaluated based on their immediate costs and benefits, their long-term performance should also be investigated. In this study, effluent quality - namely, the biological oxygen demand (BOD), chemical oxygen demand (COD), and total suspended solid (TSS) - was assessed using a biomimetics engineering approach. A novel immune network algorithm (INA) approach was applied to a septic sludge treatment plant (SSTP) for effluent-removal predictive modelling. The Matang SSTP in the city of Kuching, Sarawak, on the island of Borneo, was selected as a case study. Monthly effluent discharges from 2007 to 2011 were used for training, validating, and testing purposes using MATLAB 7.10. The results showed that the BOD effluent-discharge prediction was less than 50% of the specified standard after the 97th month of operation. The COD and TSS effluent removals were simulated at the 85th and the 121st months, respectively. The study proved that the proposed INA-based SSTP model could be used to achieve an effective SSTP assessment and management technique. This journal is © the Partner Organisations 2014.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1039/c4em00282b
dc.identifier.epage2214
dc.identifier.issue9
dc.identifier.scopus2-s2.0-84906555471
dc.identifier.spage2208
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84906555471&doi=10.1039%2fc4em00282b&partnerID=40&md5=f8874645976ce415d8bd65e98bd42bba
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22054
dc.identifier.volume16
dc.publisherRoyal Society of Chemistryen_US
dc.sourceScopus
dc.sourcetitleEnvironmental Sciences: Processes and Impacts
dc.titlePrediction analysis of effluent removal in a septic sludge treatment plant: A biomimetics engineering approachen_US
dc.typeArticleen_US
dspace.entity.typePublication
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