Matches in SemOpenAlex for { <https://semopenalex.org/work/W3026152615> ?p ?o ?g. }
Showing items 1 to 87 of
87
with 100 items per page.
- W3026152615 abstract "In aerodynamic studies, models are essential tools for understanding complex fluid flow phenomena. However, their use can be expensive in terms of computer power and calculation time. Therefore, machine learning algorithms have become essential when it comes to analyzing uncertainty in modelling and predicting the values for new input parameters with sensitivity quantifications and in a reasonably short time. The aim of this paper is to predict the key factors in aircraft design by finding the best estimation of the dependent variable in the form of the lift to drag ratio, for any new input-dependent values in the form of Mach numbers and angle of attack. Therefore, different regressions of classical supervised learning algorithms have been applied. The statistical errors have been calculated for these regressions in order to choose the best fit for an unknown model. In addition, artificial neural networks (ANN) have been used to train the data, and to predict the ratio of lift to drag in a practical time compared to the use of experimental tests and the computational fluid dynamics (CFD) technique." @default.
- W3026152615 created "2020-05-29" @default.
- W3026152615 creator A5008885674 @default.
- W3026152615 creator A5021982247 @default.
- W3026152615 creator A5025475326 @default.
- W3026152615 creator A5063365248 @default.
- W3026152615 creator A5064139543 @default.
- W3026152615 date "2020-03-01" @default.
- W3026152615 modified "2023-09-23" @default.
- W3026152615 title "Parametric studies of aerodynamic properties of wings using various forms of machine learning" @default.
- W3026152615 cites W2021218586 @default.
- W3026152615 cites W2039240409 @default.
- W3026152615 cites W2043105755 @default.
- W3026152615 cites W2110418811 @default.
- W3026152615 cites W2136309462 @default.
- W3026152615 cites W2897250207 @default.
- W3026152615 cites W2974135165 @default.
- W3026152615 doi "https://doi.org/10.1109/iccais48893.2020.9096831" @default.
- W3026152615 hasPublicationYear "2020" @default.
- W3026152615 type Work @default.
- W3026152615 sameAs 3026152615 @default.
- W3026152615 citedByCount "0" @default.
- W3026152615 crossrefType "proceedings-article" @default.
- W3026152615 hasAuthorship W3026152615A5008885674 @default.
- W3026152615 hasAuthorship W3026152615A5021982247 @default.
- W3026152615 hasAuthorship W3026152615A5025475326 @default.
- W3026152615 hasAuthorship W3026152615A5063365248 @default.
- W3026152615 hasAuthorship W3026152615A5064139543 @default.
- W3026152615 hasConcept C105795698 @default.
- W3026152615 hasConcept C107157880 @default.
- W3026152615 hasConcept C11413529 @default.
- W3026152615 hasConcept C117251300 @default.
- W3026152615 hasConcept C119857082 @default.
- W3026152615 hasConcept C127413603 @default.
- W3026152615 hasConcept C13393347 @default.
- W3026152615 hasConcept C139002025 @default.
- W3026152615 hasConcept C146978453 @default.
- W3026152615 hasConcept C154945302 @default.
- W3026152615 hasConcept C1633027 @default.
- W3026152615 hasConcept C165231844 @default.
- W3026152615 hasConcept C21200559 @default.
- W3026152615 hasConcept C24326235 @default.
- W3026152615 hasConcept C2775924081 @default.
- W3026152615 hasConcept C33923547 @default.
- W3026152615 hasConcept C41008148 @default.
- W3026152615 hasConcept C47446073 @default.
- W3026152615 hasConcept C50644808 @default.
- W3026152615 hasConcept C527307 @default.
- W3026152615 hasConcept C72921944 @default.
- W3026152615 hasConceptScore W3026152615C105795698 @default.
- W3026152615 hasConceptScore W3026152615C107157880 @default.
- W3026152615 hasConceptScore W3026152615C11413529 @default.
- W3026152615 hasConceptScore W3026152615C117251300 @default.
- W3026152615 hasConceptScore W3026152615C119857082 @default.
- W3026152615 hasConceptScore W3026152615C127413603 @default.
- W3026152615 hasConceptScore W3026152615C13393347 @default.
- W3026152615 hasConceptScore W3026152615C139002025 @default.
- W3026152615 hasConceptScore W3026152615C146978453 @default.
- W3026152615 hasConceptScore W3026152615C154945302 @default.
- W3026152615 hasConceptScore W3026152615C1633027 @default.
- W3026152615 hasConceptScore W3026152615C165231844 @default.
- W3026152615 hasConceptScore W3026152615C21200559 @default.
- W3026152615 hasConceptScore W3026152615C24326235 @default.
- W3026152615 hasConceptScore W3026152615C2775924081 @default.
- W3026152615 hasConceptScore W3026152615C33923547 @default.
- W3026152615 hasConceptScore W3026152615C41008148 @default.
- W3026152615 hasConceptScore W3026152615C47446073 @default.
- W3026152615 hasConceptScore W3026152615C50644808 @default.
- W3026152615 hasConceptScore W3026152615C527307 @default.
- W3026152615 hasConceptScore W3026152615C72921944 @default.
- W3026152615 hasLocation W30261526151 @default.
- W3026152615 hasOpenAccess W3026152615 @default.
- W3026152615 hasPrimaryLocation W30261526151 @default.
- W3026152615 hasRelatedWork W10281163 @default.
- W3026152615 hasRelatedWork W11072042 @default.
- W3026152615 hasRelatedWork W11227692 @default.
- W3026152615 hasRelatedWork W12428677 @default.
- W3026152615 hasRelatedWork W12643492 @default.
- W3026152615 hasRelatedWork W4743715 @default.
- W3026152615 hasRelatedWork W7107392 @default.
- W3026152615 hasRelatedWork W731442 @default.
- W3026152615 hasRelatedWork W8112911 @default.
- W3026152615 hasRelatedWork W8264297 @default.
- W3026152615 isParatext "false" @default.
- W3026152615 isRetracted "false" @default.
- W3026152615 magId "3026152615" @default.
- W3026152615 workType "article" @default.