ANFIS Modelling of Carbon and Nitrogen Removal in Domestic Wastewater Treatment Plant
DOI:
https://doi.org/10.11113/jt.v67.2839Keywords:
Prediction, fuzzy inference system, neural network, parametersAbstract
Wastewater treatment plant involves highly complex and uncertain processes, which are quite difficult to forecast. However, smooth and efficient operation of the treatment plant depends on an appropriate model capable of describing accurately the dynamic nature of the system. Most of the existing models were applied to industrial wastewater treatment plants. Therefore, this paper proposed an ANFIS model for carbon and nitrogen removal in the Bunus regional sewage wastewater treatment plant, Kuala Lumpur, Malaysia. For comparison, feed-forward neural network is used. Simulation results revealed that the ANFIS model demonstrated slightly better prediction capability in all the considered variables, chemical oxygen demand (COD), suspended solids (SS) and ammonium nitrogen (NH4-N) as compared to the FFNN model, thus proving that the proposed ANFIS model is reliable and useful to the wastewater treatment plant.Â
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