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The efficiency of using artificial feedforward neural networks with a single hidden layer of eight neurons for the analysis of overload conditions of selected tramway traction substations Cover

The efficiency of using artificial feedforward neural networks with a single hidden layer of eight neurons for the analysis of overload conditions of selected tramway traction substations

Open Access
|May 2020

Abstract

This paper presents further results of research on the load variability of rectifier units for the selected tram traction substation. Actual measurements were used in the performed analysis. This time, the analysis was focused on the characteristics of maximum loads and overloads for time periods of five minutes and sixty minutes, for a number of selected cases. The second part of the article discusses the effectiveness of the use of artificial neural networks of the feedforward type with one hidden layer with eight neurons to analyse the overloads of the traction substation over a longer time scale. The obtained positive results indicate that this type of research should be continued, using different variants of artificial neural networks.

DOI: https://doi.org/10.4467/2353737XCT.18.167.9423 | Journal eISSN: 2353-737X | Journal ISSN: 0011-4561
Language: English
Page range: 119 - 131
Submitted on: Oct 11, 2018
Published on: May 23, 2020
Published by: Cracow University of Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2020 Marek Dudzik, Janusz Prusak, Sławomir Drapik, Valeriy Kuznetsov, published by Cracow University of Technology
This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 License.