DocumentCode :
2671622
Title :
A modeling method based on Multiple Kernel Learning
Author :
Wang, Shuzhou ; Li, Lianhe ; Chen, Yimei
Author_Institution :
Tianjin Key Lab. of AEEET, Tianjin Polytech. Univ., Tianjin, China
fYear :
2012
fDate :
23-25 May 2012
Firstpage :
2376
Lastpage :
2378
Abstract :
Support Vector Machine (SVM) can be applied to build simulation model of helicopter. But the parameter selection should to be done before training SVM. To avoid the problems, a dynamic modeling method for helicopter based on Multiple Kernel Learning (MKL) is proposed. It is shown by simulation that the dynamic MKL modeling method owns some advantages such as fast convergence speed, simple structure, whilst maintain the generalization precision.
Keywords :
aerospace computing; helicopters; learning (artificial intelligence); quadratic programming; support vector machines; SVM training; dynamic MKL modeling method; dynamic modeling method; helicopter simulation model; multiple kernel learning; parameter selection; support vector machine; Atmospheric modeling; Helicopters; Kernel; Mathematical model; Optimization; Support vector machines; Training; Helicopter; Multiple Kernel Learning; Simulation Model; Support Vector Machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4577-2073-4
Type :
conf
DOI :
10.1109/CCDC.2012.6244381
Filename :
6244381
Link To Document :
بازگشت