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Using Interval Singleton Type 2 Fuzzy Logic System in Corrupted Time Series Modelling

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3684))

Abstract

This paper is focused on modelling of time series data which are corrupted by noise using type 2 fuzzy logic system (FLS). Type 2 FLS in which premise or consequent membership functions are type-2 fuzzy sets, can handle rule uncertainties. Type-2 FLS is very similar to a type-1 FLS, the major structural difference being that the defuzzifier block of a type-1 FLS is replaced by the output processing block in a type-2 FLS. That block consists of type-reduction followed by defuzzification. In the simulation results, Box-Jenkin’s gas furnace time series will be demonstrated and we also compare the results of the type-2 fuzzy logic approach with the results of using only a traditional type-1 fuzzy logic approach.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Korea University, 1, 5-ka, Anam-dong, Seongbuk-ku, Seoul, 136-701, Korea

    Dong-Won Kim & Gwi-Tae Park

Authors
  1. Dong-Won Kim
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  2. Gwi-Tae Park
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Editor information

Editors and Affiliations

  1. School of Business, La Trobe University, 3086, Melbourne, Victoria, Australia

    Rajiv Khosla

  2. Centre for SMART systems Engineering Research Centre, University of Brighton, Moulsecoomb, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

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© 2005 Springer-Verlag Berlin Heidelberg

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Kim, DW., Park, GT. (2005). Using Interval Singleton Type 2 Fuzzy Logic System in Corrupted Time Series Modelling. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3684. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11554028_78

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  • DOI: https://doi.org/10.1007/11554028_78

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28897-8

  • Online ISBN: 978-3-540-31997-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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