Multi-Source Information Fusion Based on Data Driven

Abstract:

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Take data driven method as 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. The example indicated that reduced computational complexity, reduced information loss in the fusion process, and enhanced the fusion accuracy.

Info:

Periodical:

Edited by:

Zhu Zhilin & Patrick Wang

Pages:

121-126

DOI:

10.4028/www.scientific.net/AMM.40-41.121

Citation:

X. Zhang et al., "Multi-Source Information Fusion Based on Data Driven", Applied Mechanics and Materials, Vols. 40-41, pp. 121-126, 2011

Online since:

November 2010

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Price:

$35.00

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