Title :
Neuro-fuzzy modelling of wastewater treatment system
Author :
Gaya, Muhammad Sani ; Wahab, N.A. ; Sam, Y.M. ; Razali, M.C. ; Samsudin, S.I.
Author_Institution :
Dept. of Control & Instrum. Eng., Univ. Teknol. Malaysia, Skudai, Malaysia
Abstract :
Wastewater treatment system is highly uncertain and intricate system. Suitable model is a key to smooth and optimal operation of the system. The available wastewater treatment system models are too difficult to use and costly to experiment. This paper presents neuro-fuzzy modelling of wastewater treatment system. Adaptability, smoothness, effectiveness, reliability, less computational and empirical experimentation costs are some of the advantages of neuro-fuzzy approach. Simulation studies show that the proposed neuro-fuzzy technique yielded outstanding results. Thus, proven the technique is an efficient and valuable tool for modelling wastewater treatment system.
Keywords :
fuzzy neural nets; wastewater treatment; adaptability; effectiveness; intricate system; neurofuzzy modelling; reliability; smoothness; uncertain system; wastewater treatment system; Wastewater treatment system; anfis; neuro-fuzzy;
Conference_Titel :
Control System, Computing and Engineering (ICCSCE), 2012 IEEE International Conference on
Conference_Location :
Penang
Print_ISBN :
978-1-4673-3142-5
DOI :
10.1109/ICCSCE.2012.6487150