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- W2377886509 abstract "This paper establishes three layers BP neural networks model for analysis the aircraft wing flight loads with the method of combining the Bayesian regularization and BP neural networks,this neural networks can account for uncharacterized nonlinear effects while improving the capability to generalize.Neural networks were trained with one aircraft's flight data for symmetries and rolls maneuvering for load excitation,and used this trained networks for forecasting the aircraft wing flight loads.Finally,compared the neural networks forecasted results with the measured ones,the conclusion showed that this method can achieve the aircraft wing load analysis,and also have a great reference value for the research and development of a new aircraft and its flight test." @default.
- W2377886509 created "2016-06-24" @default.
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- W2377886509 date "2009-01-01" @default.
- W2377886509 modified "2023-09-23" @default.
- W2377886509 title "Application of BP Neural Networks Based on Bayesian Regularization to Aircraft Wing Loads Analysis" @default.
- W2377886509 hasPublicationYear "2009" @default.
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