Title: A situation assessment approach using support vector machines as a learning tool

Authors: Jie Lu, Bo Liu, Guangquan Zhang, Zhifeng Hao, Yanshan Xiao

Addresses: Faculty of Information Technology, University of Technology Sydney, PO Box 123, Broadway, NSW 2007, Australia. ' Faculty of Information Technology, University of Technology Sydney, PO Box 123, Broadway, NSW 2007, Australia; College of Computer Science and Engineering, South China University of Technology, Guangzhou 510640, People's Republic of China. ' Faculty of Information Technology, University of Technology Sydney, PO Box 123, Broadway, NSW 2007, Australia. ' College of Computer Science and Engineering, South China University of Technology, Guangzhou 510640, People's Republic of China. ' Guangzhou Asian Games Organizing Committee, Guangzhou 510623, People's Republic of China

Abstract: In order to assess a situation and support decision makers| awareness for the situation, this study first proposes a situation assessment model with mathematical description. It then develops a Support Vector Machine based assessment approach, which has the ability to learn the rules from the previous assessment results and generate necessary warnings for a situation. Finally, a set of experiments is conducted to illustrate and validate the proposed approach.

Keywords: decision making; situation assessment; situation awareness; support vector machines; SVM; warning systems; machine learning.

DOI: 10.1504/IJNKM.2008.018942

International Journal of Nuclear Knowledge Management, 2008 Vol.3 No.1, pp.82 - 97

Published online: 23 Jun 2008 *

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