DC Motor Benchmark with Prediction Based on Mixture of Experts
dc.contributor.author | Karban, Pavel | |
dc.contributor.author | Petrášová, Iveta | |
dc.contributor.author | Doležel, Ivo | |
dc.date.accessioned | 2023-02-06T11:00:22Z | |
dc.date.available | 2023-02-06T11:00:22Z | |
dc.date.issued | 2022 | |
dc.description.abstract | The Mixture of Experts (MoE)–based approach is applied to verify the possibility of using surrogate models for searching the optima of complex multicriteria problems with constraints. This approach can successfully solve problems when the design space is limited by a higher number of constraints and traditional methods of Design of Experiments (DoE) in conjunction with one surrogate model are not able to partition the design space acceptably enough for further prediction. The methodology is tested on a well-known DC motor benchmark, where the electromagnetic and temperature fields were solved analytically, in a simplified form. | de |
dc.description.abstract-translated | The Mixture of Experts (MoE)–based approach is applied to verify the possibility of using surrogate models for searching the optima of complex multicriteria problems with constraints. This approach can successfully solve problems when the design space is limited by a higher number of constraints and traditional methods of Design of Experiments (DoE) in conjunction with one surrogate model are not able to partition the design space acceptably enough for further prediction. The methodology is tested on a well-known DC motor benchmark, where the electromagnetic and temperature fields were solved analytically, in a simplified form. | en |
dc.format | 5 s. | cs |
dc.format.mimetype | application/pdf | |
dc.identifier.citation | KARBAN, P. PETRÁŠOVÁ, I. DOLEŽEL, I. DC Motor Benchmark with Prediction Based on Mixture of Experts. In 14th International Conference ELEKTRO, ELEKTRO 2022 : /proceedings/. Piscataway: IEEE, 2022. s. nestránkováno. ISBN: 978-1-66546-726-1 , ISSN: 2691-0616 | cs |
dc.identifier.doi | 10.1109/ELEKTRO53996.2022.9803676 | |
dc.identifier.isbn | 978-1-66546-726-1 | |
dc.identifier.issn | 2691-0616 | |
dc.identifier.obd | 43938099 | |
dc.identifier.uri | 2-s2.0-85133959297 | |
dc.identifier.uri | http://hdl.handle.net/11025/51328 | |
dc.language.iso | en | en |
dc.project.ID | SGS-2021-011/Rozvoj technik snižování řádu systému v elektrotechnických aplikacích | cs |
dc.publisher | IEEE | en |
dc.relation.ispartofseries | 14th International Conference ELEKTRO, ELEKTRO 2022 : /proceedings/ | en |
dc.rights | Plný text je přístupný v rámci univerzity přihlášeným uživatelům. | cs |
dc.rights | © IEEE | en |
dc.rights.access | restrictedAccess | en |
dc.subject.translated | Brushless DC motor | en |
dc.subject.translated | analytical model | en |
dc.subject.translated | mixture of experts (MoE) | en |
dc.subject.translated | Gaussian process | en |
dc.subject.translated | optimization | en |
dc.title | DC Motor Benchmark with Prediction Based on Mixture of Experts | en |
dc.type | konferenční příspěvek | cs |
dc.type | ConferenceObject | en |
dc.type.status | Peer-reviewed | en |
dc.type.version | publishedVersion | en |
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