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

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2671622