Volume 6 Number 6 (Jun. 2011)
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JSW 2011 Vol.6(6): 1125-1132 ISSN: 1796-217X
doi: 10.4304/jsw.6.6.1125-1132

Multi-source Information Fusion Based on Data Driven

Xin Zhang1, Li Yang1, 2, Yan Zhang1, Jinxue Sui1
1Shandong Institute of Business and Technology / School of Information and Electronic Engineering, YanTai, China
2Department of Control Engineering / Naval Aeronautical Engineering University, YanTai, China

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, decisionmaking 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.

Index Terms—Information fusion, Data driven, Principal component analytic method, rough set theory, Support Vector Machine (SVM))


Cite: Xin Zhang, Li Yang, Yan Zhang, Jinxue Sui, "Multi-source Information Fusion Based on Data Driven," Journal of Software vol. 6, no. 6, pp. 1125-1132, 2011.

General Information

ISSN: 1796-217X (Online)
Frequency: Monthly (2006-2019); Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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