Issue |
E3S Web Conf.
Volume 19, 2017
International Conference Energy, Environment and Material Systems (EEMS 2017)
|
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Article Number | 02007 | |
Number of page(s) | 4 | |
Section | Environment | |
DOI | https://doi.org/10.1051/e3sconf/20171902007 | |
Published online | 23 October 2017 |
Calibration of parameters of water supply network model using genetic algorithm
1 Opole University of Technology, ul. Prószkowska 76, 45-758 Opole, Poland
2 Miejskie Wodociągi i Kanalizacja w Kędzierzynie-Koźlu Sp. z o.o., ul. Filtrowa 14, 47-200 Kędzierzyn-Koźle, Poland
3 State Higher Vocational School in Nysa, ul. Armii Krajowej 7, 48-300 Nysa, Poland
⁎ Corresponding author: t.boczar@po.opole.pl
Computer simulation models of water supply networks are commonly applied in the water industry. As part of the research works, results of which are presented in the paper, OFF-LINE and ON-LINE calibration of water supply network model parameters using two methods was carried out and compared. The network skeleton was developed in the Epanet software. For optimization two types of dependent variables were subjected: the pressure on the node and volume flow in the network section. The first calibration method regards to application of the genetic algorithm, which is a build in plugin - “Epanet Calibrator”. The second method was related to the use of function ga, which is implemented in the MATLAB toolbox Genetic Algorithm and Direct Search. The possibilities of application of these algorithms to solve the issue of optimizing the parameters of the created model of water supply network in both cases: OFF-LINE and ON-LINE calibration was examined. An analysis of the effectiveness of the considered algorithms for different values of configuration parameters was performed. Based on the achieved results it was stated that application of the ga algorithm gives higher correlation of the calibrated values to the empirical data.
© The authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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