DocumentCode :
389658
Title :
Choosing of battle position through training support vector machines
Author :
Li, Kan ; Liu, Yu-shu
Author_Institution :
Dept. of Comput. Sci. & Eng., Beijing Inst. of Technol., China
Volume :
1
fYear :
2002
fDate :
2002
Firstpage :
18
Abstract :
The battlefield environment affects maneuvers and the war situation. We choose the battle position through a training support vector machine (SVM). We give firstly the method of two-class classification by means of SVM. Choosing of battle position is a problem of multi-class classification, so we adopt a "divide and conquer" approach to train the data set. We use recursively SVM until the result meets the condition of battle position. In the course of training the data, we use one-against-one and decision tree methods. Using the schemes, we select the suited battle position and get better effect.
Keywords :
decision trees; divide and conquer methods; learning automata; military computing; optimisation; pattern classification; battle position selection; decision tree method; divide and conquer approach; maneuvers; multi-class classification; one-against-one method; support vector machines; training algorithm; two-class classification; Classification algorithms; Computer science; Decision trees; Kernel; Pattern classification; Pattern recognition; Risk management; Support vector machine classification; Support vector machines; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7508-4
Type :
conf
DOI :
10.1109/ICMLC.2002.1176699
Filename :
1176699
Link To Document :
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