Research on Constructing Surrogate Model of Rocket Aerodynamic Discipline Using Extreme Learning Machine

被引：0
|
作者：
Peng Bo [1 ]
Bai Bing [1 ]
Wang Haibin [1 ]
WangChen [1 ]
机构：
[1] Beijing Inst Aerosp Syst Engn, Beijing, Peoples R China
来源：
2018 EIGHTH INTERNATIONAL CONFERENCE ON INSTRUMENTATION AND MEASUREMENT, COMPUTER, COMMUNICATION AND CONTROL (IMCCC 2018) | 2018年
关键词：
Surrogate Model; Extreme Learning Machine; Aerodynamic Design;
D O I：
10.1109/IMCCC.2018.00215
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In order to decrease the long time consuming of the aerodynamic numerical calculation in the multi-discipline designing of the rocket, this paper proposed a surrogate model of rocket aerodynamic based on extreme learning machine, and described the process to construct the surrogate model in detail. Based on aerodynamic surrogate model of a rocket, this paper evaluated the precision of the surrogate model with a small learning sample, and it proved that this method is very feasible and effective.
引用
收藏
页码：1028 / 1033
页数：6
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