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Two effective methods for flow-field performance forecast

  • Bao Guo Wang*
  • , Jun Hong Wu
  • , Shu Yan Liu
  • , Geng Qian
  • , Yan Ming Liu
  • *Corresponding author for this work
  • Beijing Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

Based on database established by multi-factor and multi-level design methods, two effective methods of flow-field performance forecast were proposed. One is response surface method, and the other is wavelet neural networks method. The typical examples indicate that two methods can forecast flow-field performance effectively. The results also show that wavelet neural networks method is superior to response surface method in terms of efficiency and precision.

Original languageEnglish
Pages (from-to)1763-1767
Number of pages5
JournalHangkong Dongli Xuebao/Journal of Aerospace Power
Volume25
Issue number8
Publication statusPublished - Aug 2010

Keywords

  • Flow-field forecast
  • Flow-field performance
  • Response surface method
  • Uniform experimental design
  • Wavelet neural networks

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