Modeling of Chlorine Decay using Artificial Neural Network
S.Vanitha1, C.Sivapragasam2
1Dr. S.Vanitha, Department of Civil Engineering, Kalasalingam Academy of Research and Education, Krishnankoil (Tamil Nadu), India.
2Dr. C. Sivapragasam, Center of water Technology, Department of Civil Engineering, Kalasalingam Academy of Research and Education, Krishnan Kovil, (Tamil Nadu), India.
Manuscript received on 23 November 2019 | Revised Manuscript received on 17 December 2019 | Manuscript Published on 30 December 2019 | PP: 174-176 | Volume-9 Issue-1S4 December 2019 | Retrieval Number: A10041291S419/19©BEIESP | DOI: 10.35940/ijeat.A1004.1291S419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper an attempt is made to model chlorine decay using Artificial Neural Network (ANN). Initial chlorine concentration, fast and slow reacting organic and nitrogenous compounds and reaction rate constants of the compounds are used as inputs to the ANN model and the chlorine decay at different points in the decay curve are evaluated. ANN is trained by two different methods namely single output model and multi output models. Predicted data are compared with observed using correlation coefficient. Result indicates multi output model able to model more accurately than single output model.
Keywords: Organic Compounds and Inorganic Compounds, Chlorine Decay, Modeling , Artificial Neural Network.
Scope of the Article: Artificial Life and Societies