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A New Method to Measure the Information Quality Based on Shannon Entropy

  • Research Article-Computer Engineering and Computer Science
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Abstract

When aggregating data from multi-source uncertain information, how to increase the certainty and reduce the conflict is still an open issue. This paper proposes a new method to measure information quality based on Shannon entropy, which can be used to measure the certainty or information provided by probability distributions. Furthermore, a method to obtain information quality-fused values from different probability distributions is given, which can be used to measure the conflict when fusing probability distributions. Based on them, a probability aggregation method that considers both uncertainty and conflict is developed and applied to fault diagnosis. Two examples are given to illustrate the effectiveness of the proposed method.

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Acknowledgements

The work is partially supported by National Science and Technology Major Project (Program No. 2017-V-0011-0062), Peak Experience Plan in Northwestern Polytechnical University.

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Authors and Affiliations

  1. Department of Automation, Tsinghua University, Beijing, China

    Hengqi Zhang

  2. School of Electronics and Information, Northwestern Polytechnical University, Xi’an, 710072, Shaanxi, China

    Hengqi Zhang, Wen Jiang & Xinyang Deng

  3. Peng Cheng Laboratory, Shenzhen, China

    Wen Jiang

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  1. Hengqi Zhang
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  2. Wen Jiang
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Correspondence to Wen Jiang.

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Zhang, H., Jiang, W. & Deng, X. A New Method to Measure the Information Quality Based on Shannon Entropy. Arab J Sci Eng 46, 3691–3700 (2021). https://doi.org/10.1007/s13369-020-05183-1

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