Predictive Model Based on Genetic Algorithm-Neural Network for Fatigue Performances of Pre-corroded Aluminum Alloys

نویسندگان

  • Chaohua FAN
  • Yuting HE
  • Hengxi ZHANG
  • Hongpeng LI
  • Feng LI
چکیده

In the paper, genetic algorithm is introduced in the study of network authority values of BP neural network, and a GA-NN algorithm is established. Based on this genetic algorithm-neural network method, a predictive model for fatigue performances of the pre-corroded aluminum alloys under a varied corrosion environmental spectrum was developed by means of training from the testing dada, and the fatigue performances of pre-corroded aluminum alloys can be predicted. The results indicate that genetic algorithm-neural network algorithm can be employed to predict the underlying fatigue performances of the pre-corroded aluminum alloy precisely, compared with traditional neural network.

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تاریخ انتشار 2008