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《Journal of Astronautics》 2006-01
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Gyroscopic Drift Forecasting on Least Squares Support Vector Machine

CHEN Wei~1, HU Chang-hua~1, CAO Xiao-ping~2, FAN Hong-dong~1, FANG Hua-yuan~1 (1. 302Unit, The Second Artillery Engineering Institute, Xi'an 710025, China; 2. Mechatronics and Automation School of National University of Technology, Changsha 710073, China)  
This paper researches the regression estimate algorithm with SVM. Pinpoint the problem that the training speed of the standard algorithm is slow and it is hard to solve large scale problem. To overcome this drawback, a Least Squares Support Vector Machine (LSSVM) is put forward in this paper through improving the constraint condition of standard SVM algorithm. The training speed and the ability to solve large scale problem are much improved through using LSSVM. Finally, the LSSVM is applied to forecasting the gyroscopic drift in this paper. The simulated experiment proved the algorithm is valid and acceptable, and it supplies a way to real-time forecast and fault - predict of the gyroscopic.
【CateGory Index】: TP181
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