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International Symposium on Neural Networks

ISNN 2007: Advances in Neural Networks – ISNN 2007 pp 496–504Cite as

A Fast Fuzzy Neural Modelling Method for Nonlinear Dynamic Systems

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4491))

Abstract

The identification of nonlinear dynamic systems using fuzzy neural networks is studied. A fast recursive algorithm (FRA) is proposed to select both the fuzzy regressor terms and associated parameters. In comparison with the popular orthogonal least squares (OLS) method, FRA can achieve the fuzzy neural modelling with high accuracy and less computational effort.

This work was jointly supported by the European Social Fund, the UK Engineering and Physical Sciences Research Council (EPSRC Grant GR/S85191/01).

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Author information

Authors and Affiliations

  1. School of Electronics, Electrical Engineering & Computer Science, Queen’s University Belfast, Belfast BT9 5AH, UK

    Barbara Pizzileo, Kang Li & George W. Irwin

Authors
  1. Barbara Pizzileo
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  2. Kang Li
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  3. George W. Irwin
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering (M/C 154), University of Illinois at Chicago, 851 S. Morgan Street, 60607-7053, Chicago, IL, USA

    Derong Liu

  2. School of Automation, Southeast University, 210096, Nanjing, China

    Shumin Fei

  3. Laboratory of Complex Systems, Institute of Automation, Chinese Adacemy of Sciences, 100080, Beijing, P. R. China

    Zeng-Guang Hou

  4. School of Information Science and Engineering, Northeast University, Shenyang, 110004, China

    Huaguang Zhang

  5. School of Electrical Engineering, Hohai University, Nanjing, 210098, China

    Changyin Sun

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© 2007 Springer-Verlag Berlin Heidelberg

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Pizzileo, B., Li, K., Irwin, G.W. (2007). A Fast Fuzzy Neural Modelling Method for Nonlinear Dynamic Systems. In: Liu, D., Fei, S., Hou, ZG., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4491. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72383-7_59

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  • DOI: https://doi.org/10.1007/978-3-540-72383-7_59

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72382-0

  • Online ISBN: 978-3-540-72383-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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