Open AccessResearch on prediction method of hydro-resistance of a seaplane based on BP network
Author(s) -
Xianjiao Gao,
Tao Liu,
Zhengxing Zuo,
Bin Wu
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2228/1/012018
Subject(s) - artificial neural network , resistance (ecology) , construct (python library) , computer science , nonlinear system , test (biology) , test data , data mining , machine learning , geology , ecology , paleontology , physics , quantum mechanics , biology , programming language
As one of the important hydrodynamic indexes of seaplane, resistance performance is related to the practicality and economy of a seaplane. Due to the strong nonlinearity between resistance and test variables, it is difficult to predict the response relationship between them by conventional data fitting method. This paper proposes to use BP neural network to construct the response relationship between model parameters and hydro-resistance, and so it can be used to the prediction of aircraft resistance under different conditions. The result shows that prediction error of this method is controlled within 4.4%, which meets the needs of engineering accuracy. This method can reduce the model test cost to some extent, and provide a new way for the prediction of hydro-resistance of seaplane.