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An AND-OR Fuzzy Neural Network Ship Controller Design

  • Conference paper
Neural Information Processing (ICONIP 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4234))

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Abstract

In this paper, an AND-OR fuzzy neural network (AND-OR FNN) and a piecewise optimization approach are proposed. The in-degree of neuron and the connectivity of layer are firstly defined and Zadeh’s operators are employed in order to infer the symbolic expression of every layer, the equivalent is proved between the architecture of AND-OR FNN and fuzzy weighted Mamdani inference. The main superiority is shown not only in reducing the input space, but also auto-extracting the rule base. The optimization procedure consists of GA (Genetic Algorithm) and PA (Pruning Algorithm);the AND-OR FNN ship controller system is designed based on input-output data to validate this method. Simulating results demonstrate that the number of rule base is decreased remarkably and the performance is good, illustrate the approach is practicable, simple and effective.

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Author information

Authors and Affiliations

  1. Marine Engineering College, Dalian Maritime University, Dalian, 116026, P.R. China

    Jianghua Sui & Guang Ren

Authors
  1. Jianghua Sui
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  2. Guang Ren
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Editor information

Editors and Affiliations

  1. Dept. of Computer Science and Engineering, The Chinese Univ. of Hong Kong, Shatin, N.T., Hong Kong

    Irwin King

  2. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong, New Territories,, China

    Jun Wang

  3. The Chinese University of Hong Kong, Shatin, N.T., Hong Kong

    Lai-Wan Chan

  4. Department of Computer Science and Engineering & Center for Cognitive Science, The Ohio State University, OH 43210, Columbus

    DeLiang Wang

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© 2006 Springer-Verlag Berlin Heidelberg

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Sui, J., Ren, G. (2006). An AND-OR Fuzzy Neural Network Ship Controller Design. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4234. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893295_68

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  • DOI: https://doi.org/10.1007/11893295_68

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46484-6

  • Online ISBN: 978-3-540-46485-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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