| Issue |
E3S Web Conf.
Volume 613, 2025
XI International Conference on Advanced Agritechnologies, Environmental Engineering and Sustainable Development (AGRITECH-XI 2025)
|
|
|---|---|---|
| Article Number | 03004 | |
| Number of page(s) | 7 | |
| Section | Digital Technologies and Automation in Agriculture | |
| DOI | https://doi.org/10.1051/e3sconf/202561303004 | |
| Published online | 07 February 2025 | |
A new approach to studying professionally important qualities of operator-manipulators based on machine learning
Volga State University of Technology, Lenin sq. 3, Yoshkar-Ola 424000, Russian Federation
* Corresponding author: petuhoviv@volgatech.net
This paper proposes a new approach to the evaluation of an operator-manipulator’s readiness for their labour activity. This approach is based on an unsupervised machine learning method, namely on clustering. The unsupervised machine learning methods can entirely exclude subjective factors from the evaluation cycle of an operator’s readiness for their labour activity and accordingly improve the performance of training hardware and software complexes for training operator-manipulators.
© The Authors, published by EDP Sciences, 2025
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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