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On the usage of artificial neural networks in chlorine control applications for water distribution networks with high quality water

2011; UWA Publishing; Volume: 60; Issue: 1 Linguagem: Inglês

10.2166/aqua.2011.086

1365-2087

S. Soyupak, Hürevren Kılıç, I. Ethem Karadirek, Habib Muhammetoğlu,

Water Quality Monitoring Technologies

Research Article| February 01 2011 On the usage of artificial neural networks in chlorine control applications for water distribution networks with high quality water S. Soyupak; S. Soyupak 1Department of Civil Engineering, Faculty of Engineering, Atilim University, Ankara, Turkey Tel:+ 90 312 5868320 ; Fax:+ 90 312 5868091 Search for other works by this author on: This Site PubMed Google Scholar H. Kilic; H. Kilic 2Department of Computer Engineering, Faculty of Engineering, Atilim University, Ankara, Turkey Search for other works by this author on: This Site PubMed Google Scholar I. E. Karadirek; I. E. Karadirek 3Department of Environmental Engineering, Faculty of Engineering, Akdeniz University, Antalya, Turkey Search for other works by this author on: This Site PubMed Google Scholar H. Muhammetoglu H. Muhammetoglu 3Department of Environmental Engineering, Faculty of Engineering, Akdeniz University, Antalya, Turkey Tel:+ 90 242 3106327 ; Fax:+ 90 242 3106306; E-mail: muhammetoglu@usa.net Search for other works by this author on: This Site PubMed Google Scholar Journal of Water Supply: Research and Technology-Aqua (2011) 60 (1): 51–60. https://doi.org/10.2166/aqua.2011.086 Article history Received: October 03 2009 Accepted: May 31 2010 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Share Icon Share Facebook Twitter LinkedIn Email Tools Icon Tools Cite Icon Cite Permissions Search Site Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsThis Journal Search Advanced Search Citation S. Soyupak, H. Kilic, I. E. Karadirek, H. Muhammetoglu; On the usage of artificial neural networks in chlorine control applications for water distribution networks with high quality water. Journal of Water Supply: Research and Technology-Aqua 1 February 2011; 60 (1): 51–60. doi: https://doi.org/10.2166/aqua.2011.086 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Artificial neural network (ANN) methodology has found some recent applications as efficient control tools for satisfying free residual chlorine (FRC) levels at critical locations of water distribution systems. This particular research was started to critically investigate the potential and applicability of the ANN approach as a tool for controlling FRC levels for complex water distribution systems supplied by high quality waters with low chlorine demands. Konyaalti Water Distribution System, operated by Antalya Water and Wastewater Administration, Turkey, has been selected as a pilot. The selected system is complex in structure and supplied with raw water which has high quality and low decay rate of chlorine. The study has shown that ANN models with high predictive power and precision can be developed for such water distribution systems, and that these models can be utilized for forecasting purposes. The data for model building should be collected properly if the developed ANN models are to be utilized as control instruments for FRC levels within water distribution systems. artificial neural networks, control, forecasting, free residual chlorine, water distribution © IWA Publishing 2011 You do not currently have access to this content.