Issue |
E3S Web Conf.
Volume 411, 2023
VI International Conference on Actual Problems of the Energy Complex and Environmental Protection (APEC-VI-2023)
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Article Number | 01007 | |
Number of page(s) | 7 | |
Section | Issues of the Energy Complex | |
DOI | https://doi.org/10.1051/e3sconf/202341101007 | |
Published online | 10 August 2023 |
Pre-training method in the tasks of obtaining surrogate models of gas turbine units for gas turbine electric power stations
Perm National Research Polytechnic University, 29, Komsomolsky prospect, Perm, 614990, Russian Federation
* Corresponding author: AISuslov@pstu.ru
This article focuses on the application of pre-training methods in the task of synthesizing surrogate models. The article emphasizes that pre-training significantly improves the accuracy of surrogate models and speeds up their creation process. The authors examine pre-training’s impact on various aspects of surrogate modeling of a gas turbine unit that is part of a gas turbine electric power station, such as reducing computational costs, improving the approximation of complex processes, and optimizing the model synthesis procedure. The work demonstrates specific examples that clearly show how the use of pre-training can significantly improve the performance of surrogate models and optimize the development process. Thus, the authors convincingly argue that pre-training is a key tool for increasing the efficiency of surrogate modeling, capable of significantly reducing the time, costs, and efforts required for the development and use of surrogate models in the energy sector.
© 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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