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 (2012)
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,