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Identification of Nonlinear System Based on Complex-Valued Flexible Neural Network

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Intelligent Data Engineering and Automated Learning – IDEAL 2017 (IDEAL 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10585))

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Abstract

Identification of nonlinear system could help to understand and model the internal mechanism of real complex systems. In this paper, complex-valued version of flexible neural tree (CVFNT) model is proposed to identify nonlinear systems. In order to search the optimal structure and parameters of CVFNT model, a new hybrid evolutionary method based on structure-based evolutionary algorithm and firefly algorithm is employed. Two nonlinear system identification experiments are used to test CVFNT model. The results reveal that CVFNT model performs better than the proposed real-valued neural networks.

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Acknowledgement

This work was supported by the PhD research startup foundation of Zaozhuang University (No. 2014BS13), Zaozhuang University Foundation (No. 2015YY02), and Shandong Provincial Natural Science Foundation, China (No. ZR2015PF007).

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Authors and Affiliations

  1. School of Information Science and Engineering, Zaozhuang University, Zaozhuang, China

    Lina Jia, Wei Zhang & Bin Yang

Authors
  1. Lina Jia
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  2. Wei Zhang
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  3. Bin Yang
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Corresponding author

Correspondence to Bin Yang .

Editor information

Editors and Affiliations

  1. University of Manchester, Manchester, United Kingdom

    Hujun Yin

  2. School of Electronic and Electrical Engineering, Nanjing University, Nanjiing, China

    Yang Gao

  3. Nanjing University of Aeronautics and Astronautics, Nanjing, China

    Songcan Chen

  4. Guilin University of Electronic Technology, Guilin, China

    Yimin Wen

  5. Guilin University of Electronic Technology, Guilin, China

    Guoyong Cai

  6. Guilin University of Electronic Technology, Guilin, China

    Tianlong Gu

  7. Beijing University of Posts and Telecommunications, Beijing, China

    Junping Du

  8. University of Seville, Seville, Spain

    Antonio J. Tallón-Ballesteros

  9. Southeast University, Nanjing, China

    Minling Zhang

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Jia, L., Zhang, W., Yang, B. (2017). Identification of Nonlinear System Based on Complex-Valued Flexible Neural Network. In: Yin, H., et al. Intelligent Data Engineering and Automated Learning – IDEAL 2017. IDEAL 2017. Lecture Notes in Computer Science(), vol 10585. Springer, Cham. https://doi.org/10.1007/978-3-319-68935-7_18

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  • DOI: https://doi.org/10.1007/978-3-319-68935-7_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68934-0

  • Online ISBN: 978-3-319-68935-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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