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International Conference in Swarm Intelligence

ICSI 2012: Advances in Swarm Intelligence pp 175–182Cite as

The Evaluation of Data Uncertainty and Entropy Analysis for Multiple Events

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7332))

Abstract

In this paper, data analysis for multiple facts was carried out via fuzzy entropy. The entropy for the fuzzy data with respect to multiple facts was designed through distance measure. The obtained fuzzy entropy was used to analyze the uncertainties with respect to each fact. By summarizing fuzzy entropy, data uncertainty information was limited by the total fact (n) minus one, that is, n -1. The bounded calculation of data uncertainty to each fact was also proven for multiple facts and the decision of fuzzy data to the certain fact among multiple facts has been considered with the help of fuzzy entropy calculation.

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Author information

Authors and Affiliations

  1. Dept. Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu Province, China

    Sanghyuk Lee & T. O. Ting

Authors
  1. Sanghyuk Lee
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  2. T. O. Ting
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), Peking University, Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, 100871, Beijing, China

    Ying Tan

  2. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Shenzhen City Key Laboratory of Embedded System Design, College of Computer Science and Software Engineering, Shenzhen University, 518060, Shenzhen, China

    Zhen Ji

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© 2012 Springer-Verlag Berlin Heidelberg

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Lee, S., Ting, T.O. (2012). The Evaluation of Data Uncertainty and Entropy Analysis for Multiple Events. In: Tan, Y., Shi, Y., Ji, Z. (eds) Advances in Swarm Intelligence. ICSI 2012. Lecture Notes in Computer Science, vol 7332. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31020-1_21

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  • DOI: https://doi.org/10.1007/978-3-642-31020-1_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31019-5

  • Online ISBN: 978-3-642-31020-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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