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

机译:基于信息熵的多源不完全信息系统中的信息融合

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摘要

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.
机译:随着我们进入信息时代,各个领域的数据量急剧增加,数据源的分布越来越广泛。数据丢失的相应现象越来越普遍,它导致生成不完整的多源信息系统。在这种情况下,本文的提议旨在解决粗糙集理论的局限性。我们研究了不完整多源系统中的多源融合方法。本文提出了一种基于信息熵的不完整多源系统融合方法。特别是,通过与另一种方法的比较,我们的融合方法得到了验证。此外,对六个UCI数据集进行了广泛的实验,以验证所提出方法的性能。此外,实验结果表明,多源信息融合方法明显优于其他融合方法。

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