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Uncertainty measurement for a covering information system

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Abstract

A covering information system as the generalization of an information system is an important model in the field of artificial intelligence. Uncertainty measurement is a critical evaluating tool. This paper investigates uncertainty measurement for a covering information system. The concept of information structures in a covering information system is first described by using set vectors. Then, dependence between information structures in a covering information system is introduced. Next, the axiom definition of granularity measure of uncertainty for covering information systems is proposed by means of its information structures, and based on this axiom definition, information granulation and rough entropy in a covering information system are proposed. Moreover, information entropy and information amount in a covering information system are also considered. Finally, we conduct a numerical experiment on the congressional voting records data set that comes from UCI Repository of machine learning databases, and based on this numerical experiment, effectiveness analysis from the angle of statistics is given to evaluate the performance of uncertainty measurement for a covering information system. These results will be helpful for understanding the essence of uncertainty in a covering information system.

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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 (11461005), Natural Science Foundation of Guangxi (2016GXNSFAA380045, 2016GXNSFAA380282, 2016GXNSFAA38 0286), Key Laboratory of Optimization Control and Engineering Calculation in Department of Guangxi Education and Special Funds of Guangxi Distinguished Experts Construction Engineering.

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Authors and Affiliations

  1. Key Laboratory of Complex System Optimization and Big Data Processing in Department of Guangxi Education, Yulin Normal University, Yulin, 537000, People’s Republic of China

    Zhaowen Li

  2. School of Science, Guangxi University for Nationalities, Nanning, 530006, Guangxi, People’s Republic of China

    Pengfei Zhang

  3. School of Mathematical Sciences, Soochow University, Suzhou, 215006, Jiangsu, People’s Republic of China

    Xun Ge

  4. School of Software and Information Security, Guangxi University for Nationalities, Nanning, 530006, Guangxi, People’s Republic of China

    Ningxin Xie & Gangqiang Zhang

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  1. Zhaowen Li
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  2. Pengfei Zhang
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  3. Xun Ge
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  4. Ningxin Xie
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  5. Gangqiang Zhang
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Correspondence to Zhaowen Li.

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Communicated by A. Di Nola.

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Li, Z., Zhang, P., Ge, X. et al. Uncertainty measurement for a covering information system. Soft Comput 23, 5307–5325 (2019). https://doi.org/10.1007/s00500-018-3458-5

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  • DOI: https://doi.org/10.1007/s00500-018-3458-5

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