Proceedings of the 2018 2nd International Conference on Artificial Intelligence: Technologies and Applications (ICAITA 2018)

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The Application of RBF Neural Networks for the Assessment of the Water Flow Rate in the Pipework

Authors
Andrzej Czapczuk, Jacek Dawidowicz
Corresponding Author
Andrzej Czapczuk
Available Online March 2018.
DOI
10.2991/icaita-18.2018.12How to use a DOI?
Keywords
water distribution system; RBF Neural Netowrks; the water flow rate; classification
Abstract

The water distribution system is a spatially large and complex system. Its proper functioning is determined by having been correctly developed in its design and in the hydraulic calculations. The basic purpose of the calculations is the selection of the diameters of the water pipes and the flow of water occurring, therein. This requires careful assessment of the results obtained and accuracy in the solutions applied. Issues, centred around the control of the results of the calculations, are difficult to present, algorithmically, as they are based mainly on the experience and knowledge of the designer. The authors of the present paper decided to use RBF artificial neural networks when calculating the water flow rate in particular sections of the aforementioned water pipes. In order to solve this problem, QK1 ÷ QK7 deciding classes have been defined in order to describe problems related to the water flow rate in the pipework. The RBF neural network, based on the parameters of the water pipework, selects one of the QK1 ÷ QK7 classes; this allows the process of the evaluation of the results of the hydraulic calculations, thus obtained, to be automated, albeit only partially.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 2nd International Conference on Artificial Intelligence: Technologies and Applications (ICAITA 2018)
Series
Advances in Intelligent Systems Research
Publication Date
March 2018
ISBN
10.2991/icaita-18.2018.12
ISSN
1951-6851
DOI
10.2991/icaita-18.2018.12How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - CONF
AU  - Andrzej Czapczuk
AU  - Jacek Dawidowicz
PY  - 2018/03
DA  - 2018/03
TI  - The Application of RBF Neural Networks for the Assessment of the Water Flow Rate in the Pipework
BT  - Proceedings of the 2018 2nd International Conference on Artificial Intelligence: Technologies and Applications (ICAITA 2018)
PB  - Atlantis Press
SP  - 46
EP  - 49
SN  - 1951-6851
UR  - https://doi.org/10.2991/icaita-18.2018.12
DO  - 10.2991/icaita-18.2018.12
ID  - Czapczuk2018/03
ER  -