ANN-Based Short-Term Wastewater Flow Prediction for Better WWTP Control
Affiliation:
Environmental Biotechnology Department, Silesian University of Technology
2, Akademicka str., 44-100 Gliwice, Poland
leslaw.plonka@polsl.pl
DOI:
https://doi.org/10.23939/chcht04.02.159
Attachment | Size |
---|---|
![]() | 125.02 KB |
Abstract:
This paper presents an approach to predict the amount of the wastewater which enters wastewater treatment plant, using artificial neural network. The method presented can be used to give short-term predictions of wastewater inflow-rate. The described neural network model uses a very tiny set of data commonly collected by WWTP control systems.
References:
[1] Giokas D., Vlessidis A., Angelidis M. et al.: Clean Techn., Environ. Policy, 2002, 4, 183.
https://doi.org/10.1007/s10098-002-0145-z
[2] Kim H., Yoon Y. and Kim J.: Stochastic Environ. Research and Risk Assessment, 2001, 15, 399.
https://doi.org/10.1007/s004770100078
[3] Kriger C. and Tzoneva R.: AFRICON 2007, 26-28 Oct. 2007, 1.
[4] Croft D.: http://www.croftsoft.com/library/tutorials/backprop/2005-02-18.xhtml (accessed 05 April 2009).
[5] Rojas R.: Neural Networks - a Systematic Introduction. Springer-Verlag, Berlin 1996.
https://doi.org/10.1007/978-3-642-61068-4_18
[6] Soria-Olivas E., Martin-Guerrero J., Serrano-Lopez A. et al.: Neurocomputing, 2006, 69, 909.
https://doi.org/10.1016/j.neucom.2005.04.013