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Fifty Years of Fuzzy Logic and its Applications pp 107–124Cite as

Incremental Granular Fuzzy Modeling Using Imprecise Data Streams

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 326))

Abstract

System modeling in dynamic environments needs processing of streams of sensor data and incremental learning algorithms. This paper suggests an incremental granular fuzzy rule-based modeling approach using streams of fuzzy interval data. Incremental granular modeling is an adaptive modeling framework that uses fuzzy granular data that originate from unreliable sensors, imprecise perceptions, or description of imprecise values of a variable in the form fuzzy intervals. The incremental learning algorithm builds the antecedent of functional fuzzy rules and the rule base of the fuzzy model. A recursive least squares algorithm revises the parameters of a state-space representation of the fuzzy rule consequents. Imprecision in data is accounted for using specificity measures. An illustrative example concerning the Rossler attractor is given.

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Author information

Authors and Affiliations

  1. Federal University of Lavras, Department of Engineering, Control and Automation Research Group, Minas Gerais, Brazil

    Daniel Leite

  2. University of Campinas, School of Electrical and Computer Engineering, Sao Paulo, Brazil

    Fernando Gomide

Authors
  1. Daniel Leite
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  2. Fernando Gomide
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Corresponding author

Correspondence to Daniel Leite .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Texas State University, San Marcos, Texas, USA

    Dan E. Tamir

  2. School of Computing and Information Sciences, Florida International University, Miami, Florida, USA

    Naphtali D. Rishe

  3. School of Computing and Information Sciences, The University of South Florida, Tampa, Florida, USA, and Florida International University, Miami, Florida, USA

    Abraham Kandel

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Leite, D., Gomide, F. (2015). Incremental Granular Fuzzy Modeling Using Imprecise Data Streams. In: Tamir, D., Rishe, N., Kandel, A. (eds) Fifty Years of Fuzzy Logic and its Applications. Studies in Fuzziness and Soft Computing, vol 326. Springer, Cham. https://doi.org/10.1007/978-3-319-19683-1_7

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  • DOI: https://doi.org/10.1007/978-3-319-19683-1_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19682-4

  • Online ISBN: 978-3-319-19683-1

  • eBook Packages: EngineeringEngineering (R0)

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