Gyroscopic drift combination forecasting model based on evidential reasoning

被引:0
|
作者
Hu, Chang-Hua [1 ]
Si, Xiao-Sheng [1 ]
Shi, Xiao-Hua [1 ]
机构
[1] Unit 302, Xi'an Institute of Hi.-Technol., Xi'an 710025, China
来源
Kongzhi yu Juece/Control and Decision | 2009年 / 24卷 / 02期
关键词
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
According to the advantage of Dempster-Shafer (D-S) evidence theory in information fusion, evidential reasoning(ER) and support vector regression(SVR) prediction theory are combined to build a combination forecasting model, and combination forecasting algorithm based on ER is presented. This approach can overcome the weaknesses of conventional single prediction methods, such as the low precision and limitation in application. Gyroscopic drift as an example is used to realize combination forecasting. Finally, the result proves that the forecast model and combination forecasting algorithm based on ER are feasible and effective.
引用
收藏
页码:202 / 205
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