E3S Web Conf.
Volume 216, 2020Rudenko International Conference “Methodological problems in reliability study of large energy systems” (RSES 2020)
|Number of page(s)||2|
|Published online||14 December 2020|
Reliability assurance of the thermal energy sources using the neural network modelling
1 Kazan State Power Engineering University, 420066, 51 Krasnoselskaya Street, Kazan, Russian Federation
2 Kazan National Research Technological University, 420015, 68 Karl Marx Street, Kazan, Russian Federation
* Corresponding author: firstname.lastname@example.org
A software package for neural network modelling, analysis and decision-making to improve the reliability of the heat supply system is presented. The features of heat sources and heating networks are taken into account when modelling. The trends and recommendations for improving reliability are presented.
© The Authors, published by EDP Sciences, 2020
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.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.