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Uncertainty measurement for a fuzzy set-valued information system

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Abstract

Uncertainty measurement (UM) can offer new visual angle for data analysis. A fuzzy set-valued information system (FSVIS) which means an information system (IS) where its information values are fuzzy sets. This article investigates UM for a FSVIS. First, a FSVIS is introduced. Then, the distance between two information values of each attribute in a FSVIS is founded. After that, the tolerance relation induced by a given subsystem is acquired by this distance. Moreover, the information structure of this subsystem is brought forward. Additionally, measures of uncertainty for a FSVIS are explored. Eventually, to verify the validity of these measures, statistical effectiveness analysis is carried out. The obtained results will help us understand the intrinsic properties of uncertainty in a FSVIS.

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Acknowledgements

The authors would like to thank the editors and the anonymous reviewers for their valuable comments and suggestions, which have helped immensely in improving the quality of the paper. This work is supported by National Natural Science Foundation of China (11971420), Natural Science Foundation of Guangxi (2018GXNSFDA294003, 2018GXNSFDA281028, 2018GXNSFAA294134), Guangxi Higher Education Institutions of China (Document No. [2018] 35 and [2019] 52), Guangxi Natural Science Foundation (2019AC20052), Key Laboratory of Software Engineering in Guangxi University for Nationalities (2018-18XJSY-03), Research Project of Institute of Big Data in Yulin (YJKY03) and Engineering Project of Undergraduate Teaching Reform of Higher Education in Guangxi (2017JGA179).

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Correspondence to Zhaowen Li or Ching-Feng Wen.

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Li, Z., Wang, Z., Li, Q. et al. Uncertainty measurement for a fuzzy set-valued information system. Int. J. Mach. Learn. & Cyber. 12, 1769–1787 (2021). https://doi.org/10.1007/s13042-020-01273-6

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