Li Chenggong, Jin Hongtao, Jiao Zongxiaet al. Mechanism and suppression of extraneous torque of motor driver load simulator[J]. Journal of Beijing University of Aeronautics and Astronautics, 2006, 32(02): 204-208. (in Chinese)
Citation: Wang Zhifei, Wang Hua, Jia Qinping, et al. Deflection prediction for inflatable wing based on artificial neural network[J]. Journal of Beijing University of Aeronautics and Astronautics, 2011, 37(4): 405-408. (in Chinese)

Deflection prediction for inflatable wing based on artificial neural network

  • Received Date: 14 Jan 2010
  • Publish Date: 30 Apr 2011
  • To accurately predict the deflection of loaded inflatable wing, a basic impact of influence deflection was analyzed, method of orthogonal experiment was used to ascertain the main impact of influence deflection. The main impact of influence deflection was used as intputs and deflection was used as outputs. A BP artificial network model was established by using plenty of experimental statistics as training specimens, trying to access all kinds of crytic layers and elements, choosing trainlm as optimal function.Ten predictions were done continuously aiming at every group after twelve groups of specimens were selected from experimental results. The relative error between the predicted result and the experiment result is 4.48%, and standard deviation 1.033 7. The analysis results show that the rellative error between the predicted result and the messured reslut are slight for conrete specimens, which indicates that the established artificial network model has high prediction precison.

     

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