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Project detail
Duration: 01.01.2011 — 31.12.2011
Funding resources
Brno University of Technology - Vnitřní projekty VUT
- whole funder (2011-01-01 - 2011-12-31)
On the project
This project presents the application of Artificial Neural Networks (ANN) models for the purpose of forecasting chlorine decay at selected points of a water distribution network. Resent investigation about the water quality have shown the need of use non-linear modelling for chlorine decay prediction. Chlorine decay in a pipeline is a complex phenomenon so it requires techniques that can provide reliable and efficient respresentation of the complexity of this behavior.
Description in CzechThis project presents the application of Artificial Neural Networks (ANN) models for the purpose of forecasting chlorine decay at selected points of a water distribution network. Resent investigation about the water quality have shown the need of use non-linear modelling for chlorine decay prediction. Chlorine decay in a pipeline is a complex phenomenon so it requires techniques that can provide reliable and efficient respresentation of the complexity of this behavior.
KeywordsChlorine Decay; Water Distribution System; Monte Carlo; Neural Networks
Key words in CzechChlorine Decay; Water Distribution System; Monte Carlo; Neural Networks
Mark
FAST-J-11-3
Default language
English
People responsible
Tuhovčák Ladislav, doc. Ing., CSc. - fellow researcherCuesta Cordoba Gustavo Andres, Ing., Ph.D. - principal person responsible
Units
Institute of Municipal Water Management- (2012-01-01 - 2012-12-31)Faculty of Civil Engineering- (2012-01-01 - 2012-12-31)
Results
CUESTA CORDOBA, G. Development of a neural model for forecasting residual chlorine decay - Našiměřice, Czech Republic case study. In JUNIORSTAV 2012. 1. Brno, ČR: VUT v Brně, Fakulta stavební, 2012. p. 313-320. ISBN: 978-80-214-4393-8.Detail
CUESTA CORDOBA, G.; TUHOVČÁK, L.; TAUŠ, M. Using artificial neural network models to assess water quality in water distribution networks. In PROCEDIA ENGINEERING, volume 70. Procedia Engineering. Philadelphia, USA: Elsevier, 2014. p. 399-408. ISSN: 1877-7058.Detail
KUČERA, T. Recenze na článek Development of a neural model for forecasting residual chlorine decay - Našiměřice, Czech Republic case study - doktoranda Ing. Gustava Andrese Cuesta Cordoby (Apollo 97000). Brno, ČR: VUT v Brně, Fakulta stavební, 2012.Detail