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Learning of Type-2 Fuzzy Logic Systems by Simulated Annealing with Adaptive Step Size

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Electrical Engineering and Intelligent Systems

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 130))

Abstract

In this paper, a combination of an interval type-2 fuzzy logic system (IT2FLS) models and simulated annealing is used to predict the Mackey–Glass time series by searching for the best configuration of the IT2FLS. Simulated annealing is used to learn the parameters of the antecedent and the consequent parts of the rules for a Mamdani model. Simulated annealing is combined with a method to reduce the computations associated with it using adaptive step sizes. The results of the proposed methods are compared to results of a type-1 fuzzy logic system (T1FLS).

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Authors and Affiliations

  1. The Centre for Computational Intelligence, De Montfort University, Leicester, LE1 9BH, UK

    Majid Almaraashi, Robert John & Samad Ahmadi

Authors
  1. Majid Almaraashi
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  2. Robert John
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  3. Samad Ahmadi
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Corresponding author

Correspondence to Majid Almaraashi .

Editor information

Editors and Affiliations

  1. International Association of Engineers, Unit 1, 1/F, 37-39 Hung To Road, Hong Kong, China

    Sio-Iong Ao

  2. School of Engineering, Applied Mathematics and Computing, Cranfield University, College Road, Cranfield, MK43 0AL, Bedfordshire, United Kingdom

    Len Gelman

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Almaraashi, M., John, R., Ahmadi, S. (2013). Learning of Type-2 Fuzzy Logic Systems by Simulated Annealing with Adaptive Step Size. In: Ao, SI., Gelman, L. (eds) Electrical Engineering and Intelligent Systems. Lecture Notes in Electrical Engineering, vol 130. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-2317-1_5

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  • DOI: https://doi.org/10.1007/978-1-4614-2317-1_5

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-2316-4

  • Online ISBN: 978-1-4614-2317-1

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