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Fuzzy Relation-Based Polynomial Neural Networks Based on Hybrid Optimization

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Advances in Neural Networks – ISNN 2012 (ISNN 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7367))

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Abstract

This paper introduces hybrid optimized fuzzy relation-based polynomial neural network (HOFRPNN), a novel architecture that is constructed by using a combination of fuzzy rule-based models, polynomial neural networks (PNNs) and a hybrid optimization algorithm. The proposed hybrid optimization algorithm is developed by a combination of a space search algorithm and an improved complex method. The structure of HOFRPNN comprises of a synergistic usage of fuzzy-rule-based polynomial neuron that are essentially fuzzy rule-based models and polynomial neural networks that is an extended group method of data handling (GMDH). The architecture of HOFRPNN is an essentially modified PNN whose basic nodes are fuzzy-rule-based polynomial neurons rather than conventional polynomial neurons. Moreover, the hybrid optimization algorithm is utilized to optimize the structure topology of HOFRPNN. A comparative study demonstrates that the proposed model exhibits higher accuracy and superb predictive capability when compared with some previous models reported in the literature.

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Author information

Authors and Affiliations

  1. School of Computer and Communication Engineering, Tianjin University of Technology, Tianjin, 300191, China

    Wei Huang

  2. Department of Electrical Engineering, The University of Suwon, San 2-2, Wau-ri, Bongdam-eup, Hwaseong-si, Gyeonggi-do, 445-743, South Korea

    Sung-Kwun Oh

Authors
  1. Wei Huang
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  2. Sung-Kwun Oh
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Editor information

Editors and Affiliations

  1. Department of Mechanical & Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong

    Jun Wang

  2. School of Electrical and Computer Engineering, Oklahoma State University, 74078, Stillwater, OK, USA

    Gary G. Yen

  3. Department of Electrical and Computer Engineering, University of Cyprus, 75 Kallipoleos Avenue, 1678, Nicosia, Cyprus

    Marios M. Polycarpou

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© 2012 Springer-Verlag Berlin Heidelberg

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Huang, W., Oh, SK. (2012). Fuzzy Relation-Based Polynomial Neural Networks Based on Hybrid Optimization. In: Wang, J., Yen, G.G., Polycarpou, M.M. (eds) Advances in Neural Networks – ISNN 2012. ISNN 2012. Lecture Notes in Computer Science, vol 7367. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31346-2_11

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  • DOI: https://doi.org/10.1007/978-3-642-31346-2_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31345-5

  • Online ISBN: 978-3-642-31346-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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