Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Olkhovskiy, Mikhail | |
| dc.contributor.author | Müllerová, Eva | |
| dc.contributor.author | Martínek, Petr | |
| dc.date.accessioned | 2022-12-05T11:00:18Z | - |
| dc.date.available | 2022-12-05T11:00:18Z | - |
| dc.date.issued | 2022 | |
| dc.identifier.citation | OLKHOVSKIY, M. MÜLLEROVÁ, E. MARTÍNEK, P. Comparison of One-Dimensional and Two-Dimensional Reference Signal Representation for Insulation Aging State Recognition. In Proceedings of the 2022 International Conference on Diagnostics in Electrical Engineering (Diagnostika) : CDEE 2022. Pilsen: University of West Bohemia in Pilsen, 2022. s. nestránkováno. ISBN: 978-1-66548-082-6 | cs |
| dc.identifier.isbn | 978-1-66548-082-6 | |
| dc.identifier.uri | 2-s2.0-85141397372 | |
| dc.identifier.uri | http://hdl.handle.net/11025/50534 | |
| dc.format | 4 s. | cs |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en | en |
| dc.publisher | University of West Bohemia in Pilsen | en |
| dc.relation.ispartofseries | Proceedings of the 2022 International Conference on Diagnostics in Electrical Engineering (Diagnostika) : CDEE 2022 | en |
| dc.rights | © IEEE | en |
| dc.title | Comparison of One-Dimensional and Two-Dimensional Reference Signal Representation for Insulation Aging State Recognition | en |
| dc.type | konferenční příspěvek | cs |
| dc.type | ConferenceObject | en |
| dc.rights.access | openAccess | en |
| dc.type.version | publishedVersion | en |
| dc.description.abstract-translated | This paper compares the performance of one-dimensional and two-dimensional convolutional neural networks in the task of analyzing a reference signal while determining the degradation level of single-core polymer-insulated cable. In this work was designed the set of reference signals and several forms of representing of these signals in the form of one-dimensional and two-dimensional tensors. Then, an experimental determination of the most effective version of the reference signal is carried out in terms of classification accuracy and the most effective form of representation of this signal was found, as well as most efficient type of neural network. | en |
| dc.subject.translated | one-dimensional neural networks | en |
| dc.subject.translated | convolutional networks | en |
| dc.subject.translated | reference signal processing | en |
| dc.subject.translated | signal analysis | en |
| dc.subject.translated | cable insulation | en |
| dc.subject.translated | classification accuracy | en |
| dc.identifier.doi | 10.1109/Diagnostika55131.2022.9905173 | |
| dc.type.status | Peer-reviewed | en |
| dc.identifier.obd | 43937044 | |
| dc.project.ID | SGS-2021-018/Analýza, simulace a pokročilé vyhodnocení dodávky a spotřeby elektrické energie při dodržení optimálních spolehlivostních a kvalitativních parametrů s respektováním integrace obnovitelných zdrojů, akumulace a elektromobility do elektrizační soustavy při využití aktuálních, inovativních metod teoretického a aplikačního výzkumu v elektroenergetice | cs |
| Appears in Collections: | OBD | |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| Mullerova_Comparison_of_One-Dimensional.pdf | 2,02 MB | Adobe PDF | View/Open |
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