| Issue |
E3S Web Conf.
Volume 224, 2020
Topical Problems of Agriculture, Civil and Environmental Engineering (TPACEE 2020)
|
|
|---|---|---|
| Article Number | 01018 | |
| Number of page(s) | 6 | |
| Section | Mathematical Models for Environmental Monitoring and Assessment | |
| DOI | https://doi.org/10.1051/e3sconf/202022401018 | |
| Published online | 23 December 2020 | |
Analysis of neural network results based on experimental data during indentation
Don State Technical University, 1 Gagarin square, Rostov-on-Don, 344000, Russia
* Corresponding author: copybird@yandex.ru
The article is devoted to the development of machine learning methods for classes of technical problems, including determining the properties of materials. According to the authors, the neural network approximation algorithm is able to take into account the behavior of materials in various experimental conditions. The article provides illustrative examples of how a neural network with a single hidden layer can approximate a function of several variables with a given accuracy. As part of the study, a number of experimental measurements were made. The structure of the neural network and its main components are described.
© 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.
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