基于神经网络算法的发射场坪承载能力预测方法

Mingjun Li, Yi Jiang*, Liqi Ma, Xiao Pan

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

1 引用 (Scopus)

摘要

A rapid prediction method of the bearing capacity of launching site is proposed to improve the quick response ability of the missile launching, which is based on linear multiple regression algorithm, back propagation(BP) algorithm and radial basis function (RBF) algorithm. An optimized Latin hypercube sampling method with parameter sensitivity is applied to construct the sample space. The approximate models evaluated by different algorithms under different loads are established and proved to be effective. Evaluation algorithm of the bearing capacity of unknown launching site is established to predict the probable maximum deflection under launch load using dynamical response of the launching site under erection load. The results show that the RBF algorithm has the best prediction performance and the regression coefficients under erection and launch loads are 0.941 and 0.983.The average error between predicted and simulated results is 10.46%. For the launching site with higher bearing capacity, the residual error of the evaluation algorithm ranges in ±2 mm.

投稿的翻译标题The Prediction Method Based on Neural Network Algorithm for the Bearing Capacity of Launching Site
源语言繁体中文
页(从-至)982-991
页数10
期刊Binggong Xuebao/Acta Armamentarii
43
5
DOI
出版状态已出版 - 5月 2022

关键词

  • Back propagation
  • Launching site
  • Linear multiple regression algorithm
  • Prediction of the bearing capacity
  • Radial basis function

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