Modeling of the activated sludge process by using artificial neural networks with automated architecture screening

MORAL H., AKSOY A., Golcay C. F.

COMPUTERS & CHEMICAL ENGINEERING, cilt.32, sa.10, ss.2471-2478, 2008 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 32 Sayı: 10
  • Basım Tarihi: 2008
  • Doi Numarası: 10.1016/j.compchemeng.2008.01.008
  • Dergi Adı: COMPUTERS & CHEMICAL ENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.2471-2478
  • Anahtar Kelimeler: activated sludge process, artificial intelligence, artificial neural networks, modeling, WATER TREATMENT-PLANT, WASTE-WATER, PREDICTION, SIMULATION
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

In this study, a MATLAB script was developed to aid in the development of artificial neural network (ANN) models by Screening Out the better ANN architectures for the cases studied. Then, the script was applied for modeling of activated sludge process (ASP) for two different cases. In the first one, a hypothetical wastewater treatment plant (WWTP) was considered. The input and Output data for the training of the ANN models were generated using a simulation model, which was an implementation of the Activated Sludge Model No. 1 (ASM 1). The results indicated high correlation coefficient (R) between the observed and predicted output variables, reaching up to 0.980. In the second case, ANN modeling of ASP in the Iskenderun Wastewater Treatment Plant (IskWWTP) was studied. Resulting maximum R value was 0.795 for the predicted effluent chemical oxygen demand (CODeff) Values. Moreover, CODeff was forecasted using another effluent parameter. (c) 2008 Elsevier Ltd. All rights reserved.