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Effect of training data changing step and input vector excessive dimension of a neural network on approximation accuracy. Load calculation of a unstable communication line
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| dc.contributor.author | PENIN, Alexandr | |
| dc.contributor.author | SIDORENKO, Anatolie | |
| dc.date.accessioned | 2024-04-26T08:39:04Z | |
| dc.date.available | 2024-04-26T08:39:04Z | |
| dc.date.issued | 2024 | |
| dc.identifier.citation | PENIN, Alexandr, SIDORENKO, Anatolie. Effect of training data changing step and input vector excessive dimension of a neural network on approximation accuracy. Load calculation of a unstable communication line. In: Quo Vadis – Ethics of the Scientific Research: conf. NANO-2024, event devoted to the 60th anniversary of the Technical University of Moldova, 15-18 April 2024, Chişinău, Republica Moldova: Program and proceedings of the conference, Chişinău 2024, pp. 115-117. ISBN 978-9975-64-422-8. | en_US |
| dc.identifier.isbn | 978-9975-64-422-8 | |
| dc.identifier.uri | http://repository.utm.md/handle/5014/26943 | |
| dc.description.abstract | The machine and especially deep learning do not have a powerful mathematical platform and are based almost exclusively on engineering solutions. It is a practical discipline in which ideas are often proven empirically rather than theoretically. One of the applications of neural networks are the approximation or regression tasks. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Technical University of Moldova | en_US |
| dc.relation.ispartofseries | NANO-2024 "Quo Vadis – Ethics of the Scientific Research", event devoted to the 60th anniversary of the Technical University of Moldova;15-18 April 2024, Chişinău, Republica Moldova | |
| dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
| dc.subject | machine learning | en_US |
| dc.subject | neural networks | en_US |
| dc.subject | approximation tasks | en_US |
| dc.subject | regression tasks | en_US |
| dc.title | Effect of training data changing step and input vector excessive dimension of a neural network on approximation accuracy. Load calculation of a unstable communication line | en_US |
| dc.type | Article | en_US |
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