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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering, Engineering, Electrical & Electronic


eISSN: 1178-5608



VOLUME 6 , ISSUE 3 (June 2013) > List of articles


M.S. Gaya * / N. A. Wahab * / Y. M. Sam * / A.N Anuar / S.I. Samsuddin / M.C Razali

Keywords : Model, pollutants, neuro-fuzzy, anfis, parameters.

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 6, Issue 3, Pages 1,167-1,179, DOI: https://doi.org/10.21307/ijssis-2017-585

License : (CC BY-NC-ND 4.0)

Received Date : 10-March-2013 / Accepted: 14-May-2013 / Published Online: 05-June-2013



Activated sludge system is the essential technology in use for municipal wastewater treatment plant. The system design for pollutants removal, safety analysis and experimentation relied upon an effective, straightforward and reliable model. However, most of the available models are too complex to use for control purposes either practically or via simulation. Therefore, vehement need for a simplistic and efficient model could not be avoided. This paper presents a simplified model structure for an
activated sludge system using neuro-fuzzy system. Efficiency, ease of use, effectiveness and fast convergence are some of the alluring qualities of neuro-fuzzy technique. Building a reliable and flexible model requires validation with full scale or experimental data. Therefore, with the use of the full-scale data from the domestic wastewater treatment plant in Malaysia, the validation was achieved. For comparison, auto regressive with exogenous input (ARX) model was used. Simulation studies showed that the proposed method produced promising results, thus revealing the technique is effective and robust in modelling the activated sludge system.

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