Two effective methods for flow-field performance forecast

WANG Bao-guo; WU Jun-hong; LIU Shu-yan; QIAN Geng; LIU Yan-ming

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Two effective methods for flow-field performance forecast

更新时间：2026-07-07

- Two effective methods for flow-field performance forecast
- Vol. 25, Issue 8, (2010)
- 作者机构：
  
  北京理工大学宇航学院,北京,100081
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2010
- 稿件说明：
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WANG Bao-guo, WU Jun-hong, LIU Shu-yan, et al. Two effective methods for flow-field performance forecast[J]. 2010, 25(8).
DOI：

WANG Bao-guo, WU Jun-hong, LIU Shu-yan, et al. Two effective methods for flow-field performance forecast[J]. 2010, 25(8). DOI：

摘要

在多因素多水平试验设计方法建立数据库的基础上

提出了预测流场特性的两类高效方法:一类是响应面方法;一类是小波神经网络方法.典型算例表明

两类方法都可以高效率的获取流场特性参数

而且在预测的精度与计算的效率上

小波神经网络方法较响应面方法更具有优势.

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.

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Related Institution

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