Matches in SemOpenAlex for { <https://semopenalex.org/work/W4367016727> ?p ?o ?g. }
Showing items 1 to 84 of
84
with 100 items per page.
- W4367016727 endingPage "1936" @default.
- W4367016727 startingPage "1932" @default.
- W4367016727 abstract "In this letter, a machine-learning-assisted antenna optimization method is proposed based on the random forest (RF) algorithm with data augmentation (DA). Using only a small number of samples, the prediction and optimization accuracy of the RF algorithm is ensured with repeated DA, which balances different types of samples during the training. With the proposed DA-RF method, the AR bandwidth of a circularly polarized omnidirectional base station antenna is optimized. By learning the relationship between the loop orientations and the AR bandwidth efficiently, the AR bandwidth is improved by 41% compared with the best one in the samples. The estimation accuracy of the proposed method outperforms other similar methods, with fewer iterations as well. The method is also successfully applied to multi-objective optimizations." @default.
- W4367016727 created "2023-04-27" @default.
- W4367016727 creator A5030841645 @default.
- W4367016727 creator A5041762642 @default.
- W4367016727 creator A5073212256 @default.
- W4367016727 creator A5087641204 @default.
- W4367016727 date "2023-08-01" @default.
- W4367016727 modified "2023-10-14" @default.
- W4367016727 title "Machine-Learning-Assisted Antenna Optimization With Data Augmentation" @default.
- W4367016727 cites W2795806507 @default.
- W4367016727 cites W2911964244 @default.
- W4367016727 cites W2921489899 @default.
- W4367016727 cites W2968635623 @default.
- W4367016727 cites W2977014839 @default.
- W4367016727 cites W2982158167 @default.
- W4367016727 cites W2988461403 @default.
- W4367016727 cites W3035932922 @default.
- W4367016727 cites W3110931918 @default.
- W4367016727 cites W3135079324 @default.
- W4367016727 cites W3167464908 @default.
- W4367016727 cites W3208639579 @default.
- W4367016727 cites W4205684633 @default.
- W4367016727 cites W4206759889 @default.
- W4367016727 cites W4212896756 @default.
- W4367016727 cites W4214828039 @default.
- W4367016727 cites W4214901809 @default.
- W4367016727 cites W4256060553 @default.
- W4367016727 cites W4285275029 @default.
- W4367016727 doi "https://doi.org/10.1109/lawp.2023.3269811" @default.
- W4367016727 hasPublicationYear "2023" @default.
- W4367016727 type Work @default.
- W4367016727 citedByCount "1" @default.
- W4367016727 crossrefType "journal-article" @default.
- W4367016727 hasAuthorship W4367016727A5030841645 @default.
- W4367016727 hasAuthorship W4367016727A5041762642 @default.
- W4367016727 hasAuthorship W4367016727A5073212256 @default.
- W4367016727 hasAuthorship W4367016727A5087641204 @default.
- W4367016727 hasConcept C11413529 @default.
- W4367016727 hasConcept C126255220 @default.
- W4367016727 hasConcept C154945302 @default.
- W4367016727 hasConcept C169258074 @default.
- W4367016727 hasConcept C21822782 @default.
- W4367016727 hasConcept C24027999 @default.
- W4367016727 hasConcept C2776257435 @default.
- W4367016727 hasConcept C2987595161 @default.
- W4367016727 hasConcept C33923547 @default.
- W4367016727 hasConcept C41008148 @default.
- W4367016727 hasConcept C74064498 @default.
- W4367016727 hasConcept C76155785 @default.
- W4367016727 hasConceptScore W4367016727C11413529 @default.
- W4367016727 hasConceptScore W4367016727C126255220 @default.
- W4367016727 hasConceptScore W4367016727C154945302 @default.
- W4367016727 hasConceptScore W4367016727C169258074 @default.
- W4367016727 hasConceptScore W4367016727C21822782 @default.
- W4367016727 hasConceptScore W4367016727C24027999 @default.
- W4367016727 hasConceptScore W4367016727C2776257435 @default.
- W4367016727 hasConceptScore W4367016727C2987595161 @default.
- W4367016727 hasConceptScore W4367016727C33923547 @default.
- W4367016727 hasConceptScore W4367016727C41008148 @default.
- W4367016727 hasConceptScore W4367016727C74064498 @default.
- W4367016727 hasConceptScore W4367016727C76155785 @default.
- W4367016727 hasFunder F4320321001 @default.
- W4367016727 hasFunder F4320321543 @default.
- W4367016727 hasFunder F4320329895 @default.
- W4367016727 hasIssue "8" @default.
- W4367016727 hasLocation W43670167271 @default.
- W4367016727 hasOpenAccess W4367016727 @default.
- W4367016727 hasPrimaryLocation W43670167271 @default.
- W4367016727 hasRelatedWork W2118449739 @default.
- W4367016727 hasRelatedWork W2240965754 @default.
- W4367016727 hasRelatedWork W2386767533 @default.
- W4367016727 hasRelatedWork W3138849310 @default.
- W4367016727 hasRelatedWork W3208985699 @default.
- W4367016727 hasRelatedWork W4280494160 @default.
- W4367016727 hasRelatedWork W4281560664 @default.
- W4367016727 hasRelatedWork W4323021782 @default.
- W4367016727 hasRelatedWork W4367335861 @default.
- W4367016727 hasRelatedWork W4383426745 @default.
- W4367016727 hasVolume "22" @default.
- W4367016727 isParatext "false" @default.
- W4367016727 isRetracted "false" @default.
- W4367016727 workType "article" @default.