Prediction of wastewater treatment plant performance based on wavelet packet decomposition and neural networks

HANBAY D., Turkoglu I., Demir Y.

EXPERT SYSTEMS WITH APPLICATIONS, cilt.34, sa.2, ss.1038-1043, 2008 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 34 Sayı: 2
  • Basım Tarihi: 2008
  • Doi Numarası: 10.1016/j.eswa.2006.10.030
  • Dergi Adı: EXPERT SYSTEMS WITH APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1038-1043
  • Anahtar Kelimeler: wavelet packet decomposition, entropy, wastewater treatment plant, total suspended solid
  • İnönü Üniversitesi Adresli: Hayır

Özet

In this paper, an intelligent wastewater treatment plant model is developed to predict the performance of a wastewater treatment plant (WWTP). The developed model is based on wavelet packet decomposition, entropy and neural network. The data used in this work were obtained from a WWTP in Malatya, Turkey. Daily records of these WWTP parameters over a year were obtained from the plant laboratory. Wavelet packet decomposition was used to reduce the input vectors dimensions of intelligent model. The suitable architecture of the neural network model is determined after several trial and error steps. Total suspended solid is one of the measures of overall plant performance so the developed model is used to predict the total suspended solid concentration in plant effluent. According to test results, the developed model performance is at desirable level. This model is an efficient and a robust tool to predict WWTP performance. (c) 2006 Elsevier Ltd. All rights reserved.