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- Title
Information Structures and Uncertainty measures in a Hybrid Information System: Gaussian Kernel Method.
- Authors
Zeng, Jiasheng; Li, Zhaowen; Zhang, Pengfei; Wang, Pei
- Abstract
A hybrid information system is an information system where there exist varieties of data, and its information structures reflect the internal features of this kind of information system. This paper researches information structures and uncertainty measurement in an HIS based on Gaussian kernel. According to the viewpoint, an HIS is seen as a multi-source information system, and the distance under each attribute is proposed which is combined into a hybrid distance. Then, the fuzzy τ cos -equivalence relation by using Gaussian kernel that is based on this hybrid distance is obtained. Next, information structures are described via set vectors, and dependence between information structures is studied. Moreover, uncertainty measures in an HIS are investigated based on its information structures. Eventually, the optimal selection of information structures in an HIS based on δ -information granulation or δ -rough entropy is given. These studies may be useful for exploring the essence of granular computing.
- Subjects
INFORMATION storage &; retrieval systems; DATA structures; GRANULAR computing; FUZZY systems; MATHEMATICAL models
- Publication
International Journal of Fuzzy Systems, 2020, Vol 22, Issue 1, p212
- ISSN
1562-2479
- Publication type
Article
- DOI
10.1007/s40815-019-00779-8