Matches in SemOpenAlex for { <https://semopenalex.org/work/W2070884027> ?p ?o ?g. }
Showing items 1 to 85 of
85
with 100 items per page.
- W2070884027 abstract "In this paper, we propose a special Multi-class SVMs (MSVM) data fusion strategy which is applied to classify vehicle based on multiple pavement structural strain time histories. The centralized and distributed fusion strategies are applied to combine information from several data sources. In the centralized strategy, all information from several data sources is centralized and combined to construct an input space. Then a MSVM classifier is trained. In distributed schemes, the individual data sources are processed separately and modeled by using the MSVM. Then new data fusion strategies are used to combine the information from the individual MSVM to acquire the final classification outputs. Two popular Multi-class SVMs algorithms (One-against-all OAA, One-against-one OAO) are used to construct classifier based on aforementioned two fusion strategies, respectively. The results are compared between SVM-based fusion approach and single data source SVM using two MSVM algorithms, respectively. The result shows this SVM-based fusion approach significantly improves the results of classification accuracy and robustness. The proposed Multisensor data fusion methods can also be applied in other fields." @default.
- W2070884027 created "2016-06-24" @default.
- W2070884027 creator A5030629175 @default.
- W2070884027 creator A5054506269 @default.
- W2070884027 creator A5070509938 @default.
- W2070884027 creator A5086564380 @default.
- W2070884027 date "2014-06-01" @default.
- W2070884027 modified "2023-09-27" @default.
- W2070884027 title "Classification Moving Vehicle Based on Multisensor Data Using Fusion of Multi-Class SVMs Methods" @default.
- W2070884027 cites W1975826146 @default.
- W2070884027 cites W1977945493 @default.
- W2070884027 cites W2096356883 @default.
- W2070884027 cites W2109565719 @default.
- W2070884027 cites W2137641062 @default.
- W2070884027 doi "https://doi.org/10.4028/www.scientific.net/amr.945-949.1978" @default.
- W2070884027 hasPublicationYear "2014" @default.
- W2070884027 type Work @default.
- W2070884027 sameAs 2070884027 @default.
- W2070884027 citedByCount "0" @default.
- W2070884027 crossrefType "journal-article" @default.
- W2070884027 hasAuthorship W2070884027A5030629175 @default.
- W2070884027 hasAuthorship W2070884027A5054506269 @default.
- W2070884027 hasAuthorship W2070884027A5070509938 @default.
- W2070884027 hasAuthorship W2070884027A5086564380 @default.
- W2070884027 hasConcept C104317684 @default.
- W2070884027 hasConcept C119857082 @default.
- W2070884027 hasConcept C12267149 @default.
- W2070884027 hasConcept C124101348 @default.
- W2070884027 hasConcept C138885662 @default.
- W2070884027 hasConcept C153180895 @default.
- W2070884027 hasConcept C154945302 @default.
- W2070884027 hasConcept C158525013 @default.
- W2070884027 hasConcept C185592680 @default.
- W2070884027 hasConcept C199360897 @default.
- W2070884027 hasConcept C2780801425 @default.
- W2070884027 hasConcept C33954974 @default.
- W2070884027 hasConcept C41008148 @default.
- W2070884027 hasConcept C41895202 @default.
- W2070884027 hasConcept C55493867 @default.
- W2070884027 hasConcept C63479239 @default.
- W2070884027 hasConcept C95623464 @default.
- W2070884027 hasConceptScore W2070884027C104317684 @default.
- W2070884027 hasConceptScore W2070884027C119857082 @default.
- W2070884027 hasConceptScore W2070884027C12267149 @default.
- W2070884027 hasConceptScore W2070884027C124101348 @default.
- W2070884027 hasConceptScore W2070884027C138885662 @default.
- W2070884027 hasConceptScore W2070884027C153180895 @default.
- W2070884027 hasConceptScore W2070884027C154945302 @default.
- W2070884027 hasConceptScore W2070884027C158525013 @default.
- W2070884027 hasConceptScore W2070884027C185592680 @default.
- W2070884027 hasConceptScore W2070884027C199360897 @default.
- W2070884027 hasConceptScore W2070884027C2780801425 @default.
- W2070884027 hasConceptScore W2070884027C33954974 @default.
- W2070884027 hasConceptScore W2070884027C41008148 @default.
- W2070884027 hasConceptScore W2070884027C41895202 @default.
- W2070884027 hasConceptScore W2070884027C55493867 @default.
- W2070884027 hasConceptScore W2070884027C63479239 @default.
- W2070884027 hasConceptScore W2070884027C95623464 @default.
- W2070884027 hasLocation W20708840271 @default.
- W2070884027 hasOpenAccess W2070884027 @default.
- W2070884027 hasPrimaryLocation W20708840271 @default.
- W2070884027 hasRelatedWork W1483596504 @default.
- W2070884027 hasRelatedWork W1496161243 @default.
- W2070884027 hasRelatedWork W1558785121 @default.
- W2070884027 hasRelatedWork W1585076845 @default.
- W2070884027 hasRelatedWork W1882152537 @default.
- W2070884027 hasRelatedWork W1985487944 @default.
- W2070884027 hasRelatedWork W1988482282 @default.
- W2070884027 hasRelatedWork W1996804002 @default.
- W2070884027 hasRelatedWork W1997261860 @default.
- W2070884027 hasRelatedWork W2005829528 @default.
- W2070884027 hasRelatedWork W2021797534 @default.
- W2070884027 hasRelatedWork W2064505663 @default.
- W2070884027 hasRelatedWork W2102328532 @default.
- W2070884027 hasRelatedWork W2112803241 @default.
- W2070884027 hasRelatedWork W2131599501 @default.
- W2070884027 hasRelatedWork W2132105065 @default.
- W2070884027 hasRelatedWork W2150154477 @default.
- W2070884027 hasRelatedWork W2335335587 @default.
- W2070884027 hasRelatedWork W2892110150 @default.
- W2070884027 hasRelatedWork W3094781641 @default.
- W2070884027 isParatext "false" @default.
- W2070884027 isRetracted "false" @default.
- W2070884027 magId "2070884027" @default.
- W2070884027 workType "article" @default.