Using artificial neural network models to assess water quality in water distribution networks
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Date
2014-04-30
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Mark
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Elsevier
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Abstract
The purpose of the research is to assess chlorine concentration in WDS using statistical models based on ANN in combination with Monte-Carlo. This approach offers advantages in contrast to the generally use methods for modeling of chlorine decay in drinking water systems until now. The model was tested on one specific location using the hydraulic and water quality parameters such as flow, pH, temperature, etc. The model allows forecasting chlorine concentration at selected nodes of the water supply system. The results obtained in these selected nodes allow then to compare the chlorine concentration with EPANET in the system under assessment.
Článek popisuje navržený model pro posuzování koncentrace chloru ve vodovodní síti využívající statistických modelů založených na umělých neuronových sítích v kombinaci s metodou Monte-Carlo.
Článek popisuje navržený model pro posuzování koncentrace chloru ve vodovodní síti využívající statistických modelů založených na umělých neuronových sítích v kombinaci s metodou Monte-Carlo.
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Citation
Procedia Engineering. 2014, vol. 70, issue 1, p. 399-408.
https://www.sciencedirect.com/science/article/pii/S1877705814000472
https://www.sciencedirect.com/science/article/pii/S1877705814000472
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Peer-reviewed
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en
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Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 Unported
http://creativecommons.org/licenses/by-nc-nd/3.0/
http://creativecommons.org/licenses/by-nc-nd/3.0/