dc.contributor.author | Li, Hui | |
dc.coverage.spatial | Минск | ru |
dc.date.accessioned | 2019-05-17T12:13:11Z | |
dc.date.available | 2019-05-17T12:13:11Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Li, Hui. Abnormal condition identification modeling based on fuzzy Bayesian network and transfer learning / Hui Li // Новые горизонты - 2018 : сборник материалов Белорусско-Китайского молодежного инновационного форума, 15-16 ноября 2018 г. : в 2 т. – Минск : БНТУ, 2018. – Т. 2. – С. 118-119. | ru |
dc.identifier.uri | https://rep.bntu.by/handle/data/52758 | |
dc.description.abstract | The abnormal condition identification model is established based on the fuzzy Bayesian network and transfer learning for the electro-fused magnesia smelting process in this paper. The data processing problem is analyzed during the process of modeling and reasoning. The proposed method owns the better performance, which lays the better foundation for making effective safe control decisions. | ru |
dc.language.iso | en | ru |
dc.publisher | БНТУ | ru |
dc.title | Abnormal condition identification modeling based on fuzzy Bayesian network and transfer learning | ru |
dc.type | Working Paper | ru |