| Issue |
E3S Web Conf.
Volume 411, 2023
VI International Conference on Actual Problems of the Energy Complex and Environmental Protection (APEC-VI-2023)
|
|
|---|---|---|
| Article Number | 01006 | |
| Number of page(s) | 7 | |
| Section | Issues of the Energy Complex | |
| DOI | https://doi.org/10.1051/e3sconf/202341101006 | |
| Published online | 10 August 2023 | |
Selection of pre-training parameters for synthesizing surrogate models of gas turbine units for gas turbine electro power stations
Perm National Research Polytechnic University, 29, Komsomolsky prospect, Perm, 614990, Russian Federation
* Corresponding author: AISuslov@pstu.ru
The article is devoted to the current task of selecting pre-training parameters for the synthesis of surrogate models, which is a key factor in creating high-performance models of complex technological objects. During the study, the authors conduct a systematic analysis of various parameters and their interactions, including determining the optimal number of training iterations, the number of trainable layers, and the number of neurons in these layers. Thanks to this approach, the results of the presented study can significantly improve the accuracy and efficiency of surrogate models, which in turn leads to simplification and acceleration of the process of their development and application in various fields of science and engineering.
© The Authors, published by EDP Sciences, 2023
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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