| 流场特性预测的两类高效方法 |
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| 引用本文： | 王保国,吴俊宏,刘淑艳,钱耕,刘艳明.流场特性预测的两类高效方法[J].航空动力学报,2010,25(8):1763-1767. |
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| 作者姓名： | 王保国 吴俊宏 刘淑艳 钱耕 刘艳明 |
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| 作者单位： | 北京理工大学,宇航学院,北京,100081 |
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| 基金项目： | 国家自然科学基金，高等学校博士学科点专项基金 |
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| 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.
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| 关 键 词： | 小波神经网络法 响应面法 均匀试验设计 流场预测 流场特性 |
| 收稿时间： | 2009/6/29 0:00:00 |
| 修稿时间： | 2009/9/15 0:00:00 |
Two effective methods for flow-field performance forecast |
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| WANG Bao-guo,WU Jun-hong,LIU Shu-yan,QIAN Geng and LIU Yan-ming.Two effective methods for flow-field performance forecast[J].Journal of Aerospace Power,2010,25(8):1763-1767. |
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| Authors: | WANG Bao-guo WU Jun-hong LIU Shu-yan QIAN Geng and LIU Yan-ming |
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| Institution: | Beijing Institute of Technology |
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| Abstract: | Based on establishing database using multi-factor and multi-level design method, two effective methods of flow-field performance forecast are 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 efficiency and precision. |
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| Keywords: | wavelet neural networks response surface method uniform experimental design flow-field forecast |
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