Matches in SemOpenAlex for { <https://semopenalex.org/work/W2076671199> ?p ?o ?g. }
Showing items 1 to 97 of
97
with 100 items per page.
- W2076671199 abstract "An ensemble of several neural networks is a convenient way to achieve better performance for a classification task. A number of methods on the basis of different techniques have been investigated for neural network ensemble (NNE) construction from early 1990s. To achieve better performance, a few hybrid NNE methods combining different individual methods are also investigated recently. This paper also presents a hybrid ensemble construction method combining boosting and negative correlation learning (NCL). The proposed method first produces a pool of predefined number of networks using standard boosting and NCL, and then genetic algorithm is used to the task of selecting an optimal subset of networks for an NNE from the pool. The proposed method builds problem-dependent adaptive NNE and shows consistently better performance with concise ensemble over the conventional methods when tested on a suite of 20 benchmark problems." @default.
- W2076671199 created "2016-06-24" @default.
- W2076671199 creator A5018767527 @default.
- W2076671199 creator A5043721074 @default.
- W2076671199 creator A5066829510 @default.
- W2076671199 date "2011-12-01" @default.
- W2076671199 modified "2023-10-11" @default.
- W2076671199 title "Hybrid neural network ensemble construction combining boosting and negative correlation learning" @default.
- W2076671199 cites W1967646346 @default.
- W2076671199 cites W1992018127 @default.
- W2076671199 cites W2058764642 @default.
- W2076671199 cites W2061119986 @default.
- W2076671199 cites W2062221817 @default.
- W2076671199 cites W2084812512 @default.
- W2076671199 cites W2097071621 @default.
- W2076671199 cites W2100128988 @default.
- W2076671199 cites W2100805904 @default.
- W2076671199 cites W2106390255 @default.
- W2076671199 cites W2112076978 @default.
- W2076671199 cites W2115405795 @default.
- W2076671199 cites W2124776405 @default.
- W2076671199 cites W2140285303 @default.
- W2076671199 cites W2152761983 @default.
- W2076671199 cites W2167055186 @default.
- W2076671199 cites W2904250082 @default.
- W2076671199 cites W2912934387 @default.
- W2076671199 cites W3009784374 @default.
- W2076671199 cites W51589798 @default.
- W2076671199 doi "https://doi.org/10.1109/iccitechn.2011.6164886" @default.
- W2076671199 hasPublicationYear "2011" @default.
- W2076671199 type Work @default.
- W2076671199 sameAs 2076671199 @default.
- W2076671199 citedByCount "1" @default.
- W2076671199 countsByYear W20766711992017 @default.
- W2076671199 crossrefType "proceedings-article" @default.
- W2076671199 hasAuthorship W2076671199A5018767527 @default.
- W2076671199 hasAuthorship W2076671199A5043721074 @default.
- W2076671199 hasAuthorship W2076671199A5066829510 @default.
- W2076671199 hasConcept C117220453 @default.
- W2076671199 hasConcept C119857082 @default.
- W2076671199 hasConcept C119898033 @default.
- W2076671199 hasConcept C13280743 @default.
- W2076671199 hasConcept C154945302 @default.
- W2076671199 hasConcept C166957645 @default.
- W2076671199 hasConcept C185798385 @default.
- W2076671199 hasConcept C205649164 @default.
- W2076671199 hasConcept C2524010 @default.
- W2076671199 hasConcept C33923547 @default.
- W2076671199 hasConcept C41008148 @default.
- W2076671199 hasConcept C45942800 @default.
- W2076671199 hasConcept C46686674 @default.
- W2076671199 hasConcept C50644808 @default.
- W2076671199 hasConcept C79581498 @default.
- W2076671199 hasConcept C95457728 @default.
- W2076671199 hasConceptScore W2076671199C117220453 @default.
- W2076671199 hasConceptScore W2076671199C119857082 @default.
- W2076671199 hasConceptScore W2076671199C119898033 @default.
- W2076671199 hasConceptScore W2076671199C13280743 @default.
- W2076671199 hasConceptScore W2076671199C154945302 @default.
- W2076671199 hasConceptScore W2076671199C166957645 @default.
- W2076671199 hasConceptScore W2076671199C185798385 @default.
- W2076671199 hasConceptScore W2076671199C205649164 @default.
- W2076671199 hasConceptScore W2076671199C2524010 @default.
- W2076671199 hasConceptScore W2076671199C33923547 @default.
- W2076671199 hasConceptScore W2076671199C41008148 @default.
- W2076671199 hasConceptScore W2076671199C45942800 @default.
- W2076671199 hasConceptScore W2076671199C46686674 @default.
- W2076671199 hasConceptScore W2076671199C50644808 @default.
- W2076671199 hasConceptScore W2076671199C79581498 @default.
- W2076671199 hasConceptScore W2076671199C95457728 @default.
- W2076671199 hasLocation W20766711991 @default.
- W2076671199 hasOpenAccess W2076671199 @default.
- W2076671199 hasPrimaryLocation W20766711991 @default.
- W2076671199 hasRelatedWork W1511510672 @default.
- W2076671199 hasRelatedWork W1557967153 @default.
- W2076671199 hasRelatedWork W1822895636 @default.
- W2076671199 hasRelatedWork W1974003465 @default.
- W2076671199 hasRelatedWork W1988664775 @default.
- W2076671199 hasRelatedWork W1989898218 @default.
- W2076671199 hasRelatedWork W2026046259 @default.
- W2076671199 hasRelatedWork W2069948547 @default.
- W2076671199 hasRelatedWork W2131593380 @default.
- W2076671199 hasRelatedWork W2135026821 @default.
- W2076671199 hasRelatedWork W2140285303 @default.
- W2076671199 hasRelatedWork W2141642853 @default.
- W2076671199 hasRelatedWork W2154615166 @default.
- W2076671199 hasRelatedWork W2358474461 @default.
- W2076671199 hasRelatedWork W2361102736 @default.
- W2076671199 hasRelatedWork W2379787794 @default.
- W2076671199 hasRelatedWork W2556155098 @default.
- W2076671199 hasRelatedWork W2999196618 @default.
- W2076671199 hasRelatedWork W2111715306 @default.
- W2076671199 hasRelatedWork W2739872841 @default.
- W2076671199 isParatext "false" @default.
- W2076671199 isRetracted "false" @default.
- W2076671199 magId "2076671199" @default.
- W2076671199 workType "article" @default.