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Multi-source Information Fusion Based on Data Driven

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Author(s): Xin Zhang | Li Yang | Yan Zhang | Jinxue Sui

Journal: Journal of Software
ISSN 1796-217X

Volume: 6;
Issue: 6;
Start page: 1125;
Date: 2011;
Original page

Keywords: Information fusion | Data driven | Principal component analytic method | rough set theory | Support Vector Machine(SVM))

ABSTRACT
Take data driven method as the theoretical basis, study multi-source information fusion technology. Using online and off-line data of the fusion system, does not rely on system's mathematical model, has avoided question about system modeling by mechanism. Uses principal component analysis method, rough set theory, Support Vector Machine(SVM) and so on, three method fusions and supplementary, through information processing and feature extraction to system's data-in, catches the most important information to lower dimensional space, realizes knowledge reduction. From data level, characteristic level, decision-making three levels realize information fusion. Through the fusion example to the data which the fire surveys to confirming, it indicated that this method reduced computational complexity, reduced information loss in the fusion process, and enhanced the fusion accuracy.
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