Study on optimization of support vectors

Author

Wu, C.G. ; Wan, L.M. ; Lee, H.P. ; Liang, Y.C.

Author_Institution

Coll. of Comput. Sci. & Technol., Jilin Univ., Changchun, China

Volume

3

fYear

2003

fDate

2-5 Nov. 2003

Firstpage

1889

Abstract

A novel method on the reduction of support vectors in the support vector machine (SVM) is presented. The reduced support vectors in the SVM are applied to the agent initial position optimization of the land combat simulation model. Numerical simulations show that the running efficiency could be increased more then 370 times employing the proposed method compared with that using the conventional SVM method under the original precision. Some experiences and trends in the study on the optimization problem are also summarized and presented.

Keywords

genetic algorithms; military computing; multi-agent systems; radial basis function networks; support vector machines; genetic algorithm; land combat simulation model; multiagent system; optimization; radial basis function neural network; support vector machine; support vectors reduction; Computational modeling; Computer science; Educational institutions; High performance computing; Jacobian matrices; Neural networks; Optimization methods; Quadratic programming; Support vector machines; Wide area networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2003 International Conference on

Print_ISBN

0-7803-8131-9

Type

conf

DOI

10.1109/ICMLC.2003.1259805

Filename

1259805