Analysis of sequence batch reactor for COD and TSS removal identification from septic sludge treatment plant using bio inspired algorithm: a case study in Sarawak

This study focuses on the prediction of effluent removal through Sequence Batch Reactor (SBR) in Septic Sludge Treatment Plant (SSTP) located in Sarawak. The SBR is a fill-and-draw activated sludge system for wastewater treatment plant. The current system practiced has successfully produced a h...

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Main Authors: Sie Chun, Ting, Ismail , Amelia Ritahani, Abdul Malik, Marlinda
Format: Conference or Workshop Item
Language:English
Published: 2012
Subjects:
Online Access:http://irep.iium.edu.my/28356/
http://irep.iium.edu.my/28356/
http://irep.iium.edu.my/28356/1/EP161%281%29.pdf
id iium-28356
recordtype eprints
spelling iium-283562013-02-13T15:31:57Z http://irep.iium.edu.my/28356/ Analysis of sequence batch reactor for COD and TSS removal identification from septic sludge treatment plant using bio inspired algorithm: a case study in Sarawak Sie Chun, Ting Ismail , Amelia Ritahani Abdul Malik, Marlinda QA75 Electronic computers. Computer science This study focuses on the prediction of effluent removal through Sequence Batch Reactor (SBR) in Septic Sludge Treatment Plant (SSTP) located in Sarawak. The SBR is a fill-and-draw activated sludge system for wastewater treatment plant. The current system practiced has successfully produced a high efficiency of effluent removal, namely Chemical Oxygen Demand (COD) and Total Suspended Solids (TSS). However, a direct cause-effect relationship to wastewater treatment performance is rarely established. Conversely, experimental results could lead to contradictory conclusions. Therefore, this hinders the formulation of deterministic cause-effect relationship that could be used as prediction model. In this study, Artificial Immune System (AIS) technique named Clonal Selection Algorithm (CSA) is introduced in the development of a prediction model to forecast the performance of the SSTP. In order to attain this objective, the Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE) and Correction Coefficient (R) are used as performance indexes. The main outcome is to achieve a satisfactory prediction of effluent removal as in accordance to “The Environmental Quality Act 1974, Environmental Quality (Sewage) Regulation 2009: Standard A” for effluent discharge. Results of this study, exhibits a small percentage of predicted effluent error successfully modeled. Thus, the pattern recognition of effluent obtained from using CSA has shown a successful novel predictive model that could be used as an engineering tool for environmental planning, 2012-11-08 Conference or Workshop Item NonPeerReviewed application/pdf en http://irep.iium.edu.my/28356/1/EP161%281%29.pdf Sie Chun, Ting and Ismail , Amelia Ritahani and Abdul Malik, Marlinda (2012) Analysis of sequence batch reactor for COD and TSS removal identification from septic sludge treatment plant using bio inspired algorithm: a case study in Sarawak. In: National Graduate Conference 2012 (NATGRAD 2012), 8-11 Novermber 2012, Selangor, Malaysia. http://natgrad2012.weebly.com/index.html
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Sie Chun, Ting
Ismail , Amelia Ritahani
Abdul Malik, Marlinda
Analysis of sequence batch reactor for COD and TSS removal identification from septic sludge treatment plant using bio inspired algorithm: a case study in Sarawak
description This study focuses on the prediction of effluent removal through Sequence Batch Reactor (SBR) in Septic Sludge Treatment Plant (SSTP) located in Sarawak. The SBR is a fill-and-draw activated sludge system for wastewater treatment plant. The current system practiced has successfully produced a high efficiency of effluent removal, namely Chemical Oxygen Demand (COD) and Total Suspended Solids (TSS). However, a direct cause-effect relationship to wastewater treatment performance is rarely established. Conversely, experimental results could lead to contradictory conclusions. Therefore, this hinders the formulation of deterministic cause-effect relationship that could be used as prediction model. In this study, Artificial Immune System (AIS) technique named Clonal Selection Algorithm (CSA) is introduced in the development of a prediction model to forecast the performance of the SSTP. In order to attain this objective, the Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE) and Correction Coefficient (R) are used as performance indexes. The main outcome is to achieve a satisfactory prediction of effluent removal as in accordance to “The Environmental Quality Act 1974, Environmental Quality (Sewage) Regulation 2009: Standard A” for effluent discharge. Results of this study, exhibits a small percentage of predicted effluent error successfully modeled. Thus, the pattern recognition of effluent obtained from using CSA has shown a successful novel predictive model that could be used as an engineering tool for environmental planning,
format Conference or Workshop Item
author Sie Chun, Ting
Ismail , Amelia Ritahani
Abdul Malik, Marlinda
author_facet Sie Chun, Ting
Ismail , Amelia Ritahani
Abdul Malik, Marlinda
author_sort Sie Chun, Ting
title Analysis of sequence batch reactor for COD and TSS removal identification from septic sludge treatment plant using bio inspired algorithm: a case study in Sarawak
title_short Analysis of sequence batch reactor for COD and TSS removal identification from septic sludge treatment plant using bio inspired algorithm: a case study in Sarawak
title_full Analysis of sequence batch reactor for COD and TSS removal identification from septic sludge treatment plant using bio inspired algorithm: a case study in Sarawak
title_fullStr Analysis of sequence batch reactor for COD and TSS removal identification from septic sludge treatment plant using bio inspired algorithm: a case study in Sarawak
title_full_unstemmed Analysis of sequence batch reactor for COD and TSS removal identification from septic sludge treatment plant using bio inspired algorithm: a case study in Sarawak
title_sort analysis of sequence batch reactor for cod and tss removal identification from septic sludge treatment plant using bio inspired algorithm: a case study in sarawak
publishDate 2012
url http://irep.iium.edu.my/28356/
http://irep.iium.edu.my/28356/
http://irep.iium.edu.my/28356/1/EP161%281%29.pdf
first_indexed 2023-09-18T20:41:51Z
last_indexed 2023-09-18T20:41:51Z
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