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Development of a Co-evolutionary Radial Basis Function Neural Classifier by a k-Random Opponents Topology

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Emerging Trends in Neuro Engineering and Neural Computation

Part of the book series: Series in BioEngineering ((SERBIOENG))

Abstract

The interest of the research in this paper is to introduce a novel competitive co-evolutionary (ComCoE) radial basis function artificial neural network (RBFANN) for data classification. The motivation is to derive a compact and accurate RBFANN by implementing an interactive “game-based” fitness evaluation within a ComCoE framework. In the CoE process, all individual RBFANNs interact with each other in an intra-specific competition. The fitness of each RBFANN is evaluated by measuring its interaction/encounter with k number of other randomly picked RBFANNs in the same population through a quantitative yet subjective manner under a k-random opponents topology. To calculate the fitness value, both the hidden nodes number and classification accuracy of each RBFANN are taken into consideration. To obtain a potential near optimal solution, the proposed model performs a global search through ComCoE approach and then performs a local search that is initiated by a scaled conjugate backpropagation algorithm to fine-tune the solution. Results from a benchmark study show high effectiveness of the co-evolved model with a k-random opponents topology in constructing an accurate yet compact network structure.

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Author information

Authors and Affiliations

  1. Faculty of Information Science and Technology, Jalan Ayer Keroh Lama, Bukit Beruang, 75450, Melaka, Malaysia

    Bee Yan Hiew & Shing Chiang Tan

  2. Faculty of Engineering and Technology, Multimedia University, Jalan Ayer Keroh Lama, Bukit Beruang, 75450, Melaka, Malaysia

    Way Soong Lim

Authors
  1. Bee Yan Hiew
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  2. Shing Chiang Tan
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  3. Way Soong Lim
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Corresponding author

Correspondence to Bee Yan Hiew .

Editor information

Editors and Affiliations

  1. Geelong Waurn Ponds Campus, Deakin University, Institute for Intelligent Systems Research and Innovation, 3216 Waurn Ponds, Victoria, Australia

    Asim Bhatti

  2. Mayo Clinic, 55905 Rochester, Minnesota, USA

    Kendall H. Lee

  3. Materials Science and Engineering, Georgia Institute of Technology, 30332-0245 Atlanta, Georgia, USA

    Hamid Garmestani

  4. Geelong Waurn Ponds Campus, Deakin University, Institute for Intelligent Systems Research and Innovation, 3216 Waurn Ponds, Victoria, Australia

    Chee Peng Lim

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Hiew, B.Y., Tan, S.C., Lim, W.S. (2017). Development of a Co-evolutionary Radial Basis Function Neural Classifier by a k-Random Opponents Topology. In: Bhatti, A., Lee, K., Garmestani, H., Lim, C. (eds) Emerging Trends in Neuro Engineering and Neural Computation. Series in BioEngineering. Springer, Singapore. https://doi.org/10.1007/978-981-10-3957-7_11

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  • DOI: https://doi.org/10.1007/978-981-10-3957-7_11

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  • Online ISBN: 978-981-10-3957-7

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