Using artificial neural network models to assess water quality in water distribution networks

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F14%3APU109680" target="_blank" >RIV/00216305:26110/14:PU109680 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.proeng.2014.02.045" target="_blank" >http://dx.doi.org/10.1016/j.proeng.2014.02.045</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.proeng.2014.02.045" target="_blank" >10.1016/j.proeng.2014.02.045</a>

Result language
angličtina
Original language name
Using artificial neural network models to assess water quality in water distribution networks
Original language description
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.
Czech name
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Czech description
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Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
20102 - Construction engineering, Municipal and structural engineering

Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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