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Article

Information Fusion in a Multi-Source Incomplete Information System Based on Information Entropy

by and *,†
School of Sciences, Chongqing University of Technology, Chongqing 400054, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Entropy 2017, 19(11), 570; https://doi.org/10.3390/e19110570
Received: 14 August 2017 / Revised: 12 October 2017 / Accepted: 19 October 2017 / Published: 17 November 2017
As we move into the information age, the amount of data in various fields has increased dramatically, and data sources have become increasingly widely distributed. The corresponding phenomenon of missing data is increasingly common, and it leads to the generation of incomplete multi-source information systems. In this context, this paper’s proposal aims to address the limitations of rough set theory. We study the method of multi-source fusion in incomplete multi-source systems. This paper presents a method for fusing incomplete multi-source systems based on information entropy; in particular, by comparison with another method, our fusion method is validated. Furthermore, extensive experiments are conducted on six UCI data sets to verify the performance of the proposed method. Additionally, the experimental results indicate that multi-source information fusion approaches significantly outperform other approaches to fusion. View Full-Text
Keywords: incomplete information system; information entropy; multi-source information fusion; rough set theory incomplete information system; information entropy; multi-source information fusion; rough set theory
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MDPI and ACS Style

Li, M.; Zhang, X. Information Fusion in a Multi-Source Incomplete Information System Based on Information Entropy. Entropy 2017, 19, 570. https://doi.org/10.3390/e19110570

AMA Style

Li M, Zhang X. Information Fusion in a Multi-Source Incomplete Information System Based on Information Entropy. Entropy. 2017; 19(11):570. https://doi.org/10.3390/e19110570

Chicago/Turabian Style

Li, Mengmeng, and Xiaoyan Zhang. 2017. "Information Fusion in a Multi-Source Incomplete Information System Based on Information Entropy" Entropy 19, no. 11: 570. https://doi.org/10.3390/e19110570

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