Journal
APPLIED MATHEMATICS AND NONLINEAR SCIENCES
Volume 8, Issue 1, Pages 319-330Publisher
WALTER DE GRUYTER GMBH
DOI: 10.2478/amns.2022.2.00013
Keywords
Nonlinear differential equation; Computer; big data; Unsteady aerodynamic force; Modeling; Wind tunnel test
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This paper studies big data classification technology and establishes a classification model that accurately predicts unsteady aerodynamic characteristics under different maneuvers using nonlinear differential equations and modeling techniques.
If you use simple linear equation classification for big data analysis and classification modeling, the work efficiency is low, and the accuracy is also poor. For this reason, the thesis uses nonlinear differential equations to carry out computer-aided unsteady aerodynamic modeling. Based on the perspective of differential equations, the big data classification technology is studied, and the classification model is established. The article constructs the differential classification mathematical model by establishing the differential equation with second-order delay and the constraint conditions of the model specification set. The article identifies and identifies linear parameters such as characteristic time constants in the aerodynamic model. Research shows that the model can accurately predict unsteady aerodynamic characteristics under different maneuvers.
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