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A New Similarity Measures on Vague Sets

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Fuzzy Information & Engineering and Operations Research & Management

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 211))

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Abstract

Vague set is a valid tool for processing uncertain information. The similarity measure of two uncertain patterns is important for intelligent reasoning. It is also a key problem to measure the similarity of vague values or vague sets in vague information processing systems. In this paper, according to the theory of similarity measure between intervals, it is shown that four factors influencing vague sets and vague values should be taken into account while calculating the similarity degree. Some existing similarity measures are reviewed and compared. Some faults of existed methods are pointed out. A new method for similarity measures between vague sets (values) is put forward, and is proved to satisfy some rules. The validity and advantage of this method are illustrated by an example.

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Acknowledgments

This work is supported by the National Scientific Fund of China (No.11161041), Fundamental Research Funds for the Central Universities (No. zyz2012081).

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Correspondence to Zheng-qi Cai .

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Cai, Zq., Shao, Yb., Tian, Sl., Cao, Yc. (2014). A New Similarity Measures on Vague Sets. In: Cao, BY., Nasseri, H. (eds) Fuzzy Information & Engineering and Operations Research & Management. Advances in Intelligent Systems and Computing, vol 211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38667-1_13

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  • DOI: https://doi.org/10.1007/978-3-642-38667-1_13

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38666-4

  • Online ISBN: 978-3-642-38667-1

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