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 language | English |
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Pages (from-to) | 1763-1767 |
Number of pages | 5 |
Journal | Hangkong Dongli Xuebao/Journal of Aerospace Power |
Volume | 25 |
Issue number | 8 |
Publication status | Published - Aug 2010 |
Keywords
- Flow-field forecast
- Flow-field performance
- Response surface method
- Uniform experimental design
- Wavelet neural networks