Matches in SemOpenAlex for { <https://semopenalex.org/work/W4378365035> ?p ?o ?g. }
Showing items 1 to 98 of
98
with 100 items per page.
- W4378365035 endingPage "2361" @default.
- W4378365035 startingPage "2353" @default.
- W4378365035 abstract "Dissolved gas analysis (DGA) has been a critical technique for transformer diagnosis. DGA is a typical multiclass imbalance problem where most of the samples correspond to healthy state transformers or units. Though numerous works have been carried out on this issue, the diagnosis accuracy is still unsatisfactory when the status of health and multiple faults are considered. Multiclass imbalance problem is also a tough task from the view of algorithm development. Previous works underestimate this issue in some sakes such as lacking investigation of the highly imbalanced dataset and lacking consideration of health data. This article presents a comprehensive study of the mentioned issues. A novel algorithm called sequential ensembled extreme learning machine (SE-ELM) is proposed. SE-ELM adopts a novel multiclass undersampling strategy followed by a sequentially updated ensemble, which achieves both accuracy and efficiency. The proposed method is validated on both an open international electrotechnical commission (IEC) dataset and a highly imbalanced private dataset. The comparison with popular algorithms proves the efficiency of SE-ELM." @default.
- W4378365035 created "2023-05-27" @default.
- W4378365035 creator A5012718640 @default.
- W4378365035 creator A5016947466 @default.
- W4378365035 creator A5025303508 @default.
- W4378365035 date "2023-10-01" @default.
- W4378365035 modified "2023-10-10" @default.
- W4378365035 title "Transformer Dissolved Gas Analysis for Highly-Imbalanced Dataset Using Multiclass Sequential Ensembled ELM" @default.
- W4378365035 cites W1563938718 @default.
- W4378365035 cites W2012276257 @default.
- W4378365035 cites W2014610539 @default.
- W4378365035 cites W2024223694 @default.
- W4378365035 cites W2051408490 @default.
- W4378365035 cites W2080850431 @default.
- W4378365035 cites W2084277209 @default.
- W4378365035 cites W2087240369 @default.
- W4378365035 cites W2088059023 @default.
- W4378365035 cites W2096553553 @default.
- W4378365035 cites W2096945460 @default.
- W4378365035 cites W2099454382 @default.
- W4378365035 cites W2104167780 @default.
- W4378365035 cites W2118978333 @default.
- W4378365035 cites W2135493362 @default.
- W4378365035 cites W2140419939 @default.
- W4378365035 cites W2295580010 @default.
- W4378365035 cites W2415033110 @default.
- W4378365035 cites W2770049107 @default.
- W4378365035 cites W2792332970 @default.
- W4378365035 cites W2902543865 @default.
- W4378365035 cites W2922656120 @default.
- W4378365035 cites W2965358732 @default.
- W4378365035 cites W2969674096 @default.
- W4378365035 cites W3110858705 @default.
- W4378365035 cites W3194488869 @default.
- W4378365035 cites W3210666031 @default.
- W4378365035 cites W3215950760 @default.
- W4378365035 cites W4210554433 @default.
- W4378365035 cites W4312307467 @default.
- W4378365035 doi "https://doi.org/10.1109/tdei.2023.3280436" @default.
- W4378365035 hasPublicationYear "2023" @default.
- W4378365035 type Work @default.
- W4378365035 citedByCount "0" @default.
- W4378365035 crossrefType "journal-article" @default.
- W4378365035 hasAuthorship W4378365035A5012718640 @default.
- W4378365035 hasAuthorship W4378365035A5016947466 @default.
- W4378365035 hasAuthorship W4378365035A5025303508 @default.
- W4378365035 hasConcept C119599485 @default.
- W4378365035 hasConcept C119857082 @default.
- W4378365035 hasConcept C12267149 @default.
- W4378365035 hasConcept C123860398 @default.
- W4378365035 hasConcept C124101348 @default.
- W4378365035 hasConcept C127413603 @default.
- W4378365035 hasConcept C136536468 @default.
- W4378365035 hasConcept C154945302 @default.
- W4378365035 hasConcept C165801399 @default.
- W4378365035 hasConcept C181335627 @default.
- W4378365035 hasConcept C2780150128 @default.
- W4378365035 hasConcept C41008148 @default.
- W4378365035 hasConcept C50644808 @default.
- W4378365035 hasConcept C66322947 @default.
- W4378365035 hasConcept C81818771 @default.
- W4378365035 hasConceptScore W4378365035C119599485 @default.
- W4378365035 hasConceptScore W4378365035C119857082 @default.
- W4378365035 hasConceptScore W4378365035C12267149 @default.
- W4378365035 hasConceptScore W4378365035C123860398 @default.
- W4378365035 hasConceptScore W4378365035C124101348 @default.
- W4378365035 hasConceptScore W4378365035C127413603 @default.
- W4378365035 hasConceptScore W4378365035C136536468 @default.
- W4378365035 hasConceptScore W4378365035C154945302 @default.
- W4378365035 hasConceptScore W4378365035C165801399 @default.
- W4378365035 hasConceptScore W4378365035C181335627 @default.
- W4378365035 hasConceptScore W4378365035C2780150128 @default.
- W4378365035 hasConceptScore W4378365035C41008148 @default.
- W4378365035 hasConceptScore W4378365035C50644808 @default.
- W4378365035 hasConceptScore W4378365035C66322947 @default.
- W4378365035 hasConceptScore W4378365035C81818771 @default.
- W4378365035 hasFunder F4320321001 @default.
- W4378365035 hasFunder F4320326707 @default.
- W4378365035 hasIssue "5" @default.
- W4378365035 hasLocation W43783650351 @default.
- W4378365035 hasOpenAccess W4378365035 @default.
- W4378365035 hasPrimaryLocation W43783650351 @default.
- W4378365035 hasRelatedWork W1671683867 @default.
- W4378365035 hasRelatedWork W2101754595 @default.
- W4378365035 hasRelatedWork W2109073422 @default.
- W4378365035 hasRelatedWork W2411489059 @default.
- W4378365035 hasRelatedWork W2417553802 @default.
- W4378365035 hasRelatedWork W2534887053 @default.
- W4378365035 hasRelatedWork W2887783772 @default.
- W4378365035 hasRelatedWork W2905251838 @default.
- W4378365035 hasRelatedWork W3134233996 @default.
- W4378365035 hasRelatedWork W4308206750 @default.
- W4378365035 hasVolume "30" @default.
- W4378365035 isParatext "false" @default.
- W4378365035 isRetracted "false" @default.
- W4378365035 workType "article" @default.