• DocumentCode
    1695128
  • 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
  • fYear
    2012
  • Firstpage
    250
  • Lastpage
    253
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control System, Computing and Engineering (ICCSCE), 2012 IEEE International Conference on
  • Conference_Location
    Penang
  • Print_ISBN
    978-1-4673-3142-5
  • Type

    conf

  • DOI
    10.1109/ICCSCE.2012.6487150
  • Filename
    6487150