Estimation of aerodynamic coefficients of a non-slender delta wing under ground effect using artific...
Estimation of aerodynamic coefficients of a non-slender delta wing under ground effect using artificial intelligence techniques
About this item
Full title
Author / Creator
Publisher
London: Springer London
Journal title
Language
English
Formats
Publication information
Publisher
London: Springer London
Subjects
More information
Scope and Contents
Contents
This work presents machine learning techniques to estimate the aerodynamic coefficients of a 40° swept delta wing under the ground effect. For this purpose, three different approaches including feed-forward neural network (FNN), Elman neural network (ENN) and adaptive neuro-fuzzy interference system (ANFIS) have been used. The optimal configuration...
Alternative Titles
Full title
Estimation of aerodynamic coefficients of a non-slender delta wing under ground effect using artificial intelligence techniques
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2680640180
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2680640180
Other Identifiers
ISSN
0941-0643
E-ISSN
1433-3058
DOI
10.1007/s00521-022-07013-x
