Performance Assessment of Advanced Biological Wastewater Treatment Plants Using Artificial Neural Networks
Öz
In this study, the application of Artificial Neural Network (ANN) techniques was used to predict the performance of wastewater treatment plant. The ANN-based model for prediction of effluent biological oxygen demand (BOD) concentrations was formed using a three-layered feed forward ANN, which used a back propagation learning algorithm. Based on the mean absolute percentage error (MAPE), the sum of the squares error (SSE), the absolute fraction of variance (R2), the root-mean-square (RMS), the coefficient of variation in percent (cov) values, and ANN models predicted effluent BOD concentration. The R2 values were found to be 94.13% and 93.18% for the training and test sets of treatment plant process, respectively. It was found that the ANN model could be employed successfully in estimating the daily BOD in the effluent of wastewater biological treatment plants.
Anahtar Kelimeler
Kaynakça
- Cinar O, Yilmaz A., “Application of Artificial Neural Network Method on Operation of Wastewater Treatment Plant: An Example Study”, KSU. Journal of Science and Engineering, 8(2): 48-52, 2011.
- Lee D S, Park JM., “Neural network modeling for on-line estimation of nutrient dynamics in a sequentially-operated batch reactor”, Journal of Biotechnology, 75: 229–239, 1999.
- Cote M, Grandijean B P, Lessard P, Yhibault J., “Dynamic modeling of the activated sludge process: improving prediction using neural networks”, Water Research, 29: 995–1004, 1995.
- Hamed M, Khalafallah M G, Hassanein E A., “Prediction of wastewater treatment plant performance using artificial neural network”, Environmental Modeling and Software, 19: 919–928, 2004.
- Wen C. H., Vassiliadis C. A., “Performing hybrid artificial intelligence techniques in wastewater treatment”, Engineering Applications of Artificial Intelligence, 11: 685-705, 1998.
- Choi D., Park H., “A hybrid Artificial Neural Network As A Software Sensor for Optimal Control of A Wastewater Treatment Process”, Water Res., 35: 3959-3967, 2001.
- Mjalli F. S., Al-Asheh S., Alfadala H. E., “Use of artificial neural network black-box modeling for the prediction of wastewater treatment plants performance”, J. Environ. Manage., 83: 329-338, 2007.
- Mingzhi H., Ma Y., Jinquan W., Yan W., “Simulation of a paper mill wastewater treatment using a fuzzy neural network”, Expert Systems with Applications, 36: 5064-5070, 2009.
Ayrıntılar
Birincil Dil
İngilizce
Konular
Mühendislik
Bölüm
Araştırma Makalesi
Yazarlar
Harun Türkmenler
Adıyaman University, Engineering Faculty, Environmental Engineering Department
Türkiye
Murat Pala
Adıyaman University, Engineering Faculty, Civil Engineering Department
Türkiye
Yayımlanma Tarihi
26 Eylül 2017
Gönderilme Tarihi
29 Haziran 2017
Kabul Tarihi
22 Eylül 2017
Yayımlandığı Sayı
Yıl 2017 Cilt: 3 Sayı: 3
Cited By
Use of Artificial Neural Network method to Predict the Amount of Oxygen in the Tigris River
IOP Conference Series: Materials Science and Engineering
https://doi.org/10.1088/1757-899X/1076/1/012033Evaluation of the effluent quality parameters of wastewater treatment plant based on uncertainty analysis and post-processing approaches (case study)
Water Science and Technology
https://doi.org/10.2166/wst.2021.067Neural Networks Algorithm for Arabic Language Features-Based Text Mining
IOP Conference Series: Materials Science and Engineering
https://doi.org/10.1088/1757-899X/1045/1/012003