<abstract xmlns="http://www.w3.org/1999/xhtml"><p> The paper explains a method for discerning the parts of a water supply system in need of renovation. The results are based on technical data collected over the last twenty one years, concerning more than two hundred sections of both renovated and nonrenovated pipelines. In the study, an appropriately prepared data set was used for training an artificial neural network (ANN) in the form of a multilayer perceptron (MLP). Further comparison between the responses of the trained MLP and the decisions made by human experts showed satisfactory consistency, although 15% of the database records produced certain discrepancies. The presented method can help create an expert system capable of supporting failure-free operation of a water distribution system.</p></abstract>

The paper explains a method for discerning the parts of a water supply system in need of renovation. The results are based on technical data collected over the last twenty one years, concerning more than two hundred sections of both renovated and nonrenovated pipelines. In the study, an appropriately prepared data set was used for training an artificial neural network (ANN) in the form of a multilayer perceptron (MLP). Further comparison between the responses of the trained MLP and the decisions made by human experts showed satisfactory consistency, although 15% of the database records produced certain discrepancies. The presented method can help create an expert system capable of supporting failure-free operation of a water distribution system.

Application of Artificial Neural Networks to the Technical Condition Assessment of Water Supply Systems

Faculty of Process and Environmental Engineering, Lodz University of Technology, ul. Wólczańska 213, 90-924 Łódź,

Company of Water Supply and Sewage Disposal Ltd., ul. Wierzbowa 52, 90-133 Łódź,

Ecological Chemistry and Engineering S

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

The paper explains a method for discerning the parts of a water supply system in need of renovation. The results are based on technical data collected over the...

Application of Artificial Neural Networks to the Technical Condition Assessment of Water Supply Systems

Publicado en línea: 12 abr 2017

Páginas: 31 - 40

DOI: https://doi.org/10.1515/eces-2017-0003

Palabras clave
water supply system, pipeline renovation, multilayer perceptron

© by Kamil Kamiński

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Application of Artificial Neural Networks to the Technical Condition Assessment of Water Supply Systems

Publicado en línea: 12 abr 2017

Páginas: 31 - 40

DOI: https://doi.org/10.1515/eces-2017-0003

Palabras clavewater supply system, pipeline renovation, multilayer perceptron

© by Kamil Kamiński

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Palabras clave
water supply system, pipeline renovation, multilayer perceptron