Prediction of the specific impulse for solid propellant rocket engine based on artificial neural network

  • Yu Xing Zhang*
  • , Zhi Ping Qiu
  • , Zhi Xin Duan
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The artificial neural networks are applied to the prediction of the specific impulse for solid propellant rocket engine. This method avoids the difficulties of concrete law analysis and the mathematical modeling. We can obtain directly the network model which contains the relation of actual system. An improved radial basis function neural networks is presented, which compensates the defect of undiscovered number of radial basis function for the traditional radial basis function neural networks. The forecast results of radial basis function neural networks and back propagation learning algorithm are compared.

Original languageEnglish
Pages (from-to)236-240+202
JournalGongcheng Lixue/Engineering Mechanics
Volume23
Issue numberSUPPL.
StatePublished - Jun 2006

Keywords

  • Back propagation learning algorithm
  • Networks learning
  • Radial basis function neural networks
  • Solid propellant rocket engine
  • Specific impulse

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