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...
| Main Authors: | , , |
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| Format: | Proceeding Paper |
| Language: | English |
| Published: |
2012
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/28356/ http://irep.iium.edu.my/28356/1/EP161%281%29.pdf |
| _version_ | 1848779954781683712 |
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| 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 |
| building | IIUM Repository |
| collection | Online Access |
| 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, |
| first_indexed | 2025-11-14T15:25:59Z |
| format | Proceeding Paper |
| id | iium-28356 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T15:25:59Z |
| publishDate | 2012 |
| recordtype | eprints |
| repository_type | Digital Repository |
| 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 Proceeding Paper 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 |
| 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 |
| 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_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_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_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 |
| topic | QA75 Electronic computers. Computer science |
| url | http://irep.iium.edu.my/28356/ http://irep.iium.edu.my/28356/ http://irep.iium.edu.my/28356/1/EP161%281%29.pdf |