IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/1965157.html
   My bibliography  Save this article

A Type-2 Fuzzy Logic Approach for Forecasting of Effluent Quality Parameters of Wastewater Treatment

Author

Listed:
  • Samyabrata Bhattacharjee
  • Khalid A. Alattas
  • Fayez F. M. El-Sousy
  • Ardashir Mohammadzadeh
  • Jihad H. Asad
  • Saleh Mobayen
  • Noorhan Alshaikh
  • Aida Mustapha

Abstract

In this investigation, we have studied and designed a type-2 fuzzy logic controller (IT2FLC) for the wastewater treatment plant at Haldia, India. To avoid modeling complex physical, chemical, and biological treatment processes of wastewater, this present work represents an ensemble of fuzzy models as surrogates for the wastewater treatment plant (WWTP). Using measured influent water quality data, each fuzzy model predicts water quality after the process of water treatment parameters. The pH, biological oxygen demand (BOD), total suspended particles (TSS), chemical oxygen demand (COD), and temperature are taken into account as input variables. Finally, the sensitivity of the IT2FLC model is evaluated by several statistical parameters like RMSE, MAE, MAPE, and most importantly R2 value. For the current model, the values of the three parameters are almost 0, whereas the value of the R2 is almost close to 1, which signifies that the IT2FLC model is accurate and more efficient in predicting response compared to other conventional methods reported in various literatures.

Suggested Citation

  • Samyabrata Bhattacharjee & Khalid A. Alattas & Fayez F. M. El-Sousy & Ardashir Mohammadzadeh & Jihad H. Asad & Saleh Mobayen & Noorhan Alshaikh & Aida Mustapha, 2022. "A Type-2 Fuzzy Logic Approach for Forecasting of Effluent Quality Parameters of Wastewater Treatment," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-10, June.
    • Handle: RePEc:hin:jnlmpe:1965157
    DOI: 10.1155/2022/1965157
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/mpe/2022/1965157.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/mpe/2022/1965157.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2022/1965157?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:1965157. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.