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 |
|---|---|
| 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
Fingerprint
Dive into the research topics of 'Two effective methods for flow-field performance forecast'. Together they form a unique fingerprint.Cite this
Wang, B. G., Wu, J. H., Liu, S. Y., Qian, G., & Liu, Y. M. (2010). Two effective methods for flow-field performance forecast. Hangkong Dongli Xuebao/Journal of Aerospace Power, 25(8), 1763-1767.