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Neuron Selection for RBF Neural Network Classifier Based on Multiple Granularities Immune Network

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3971))

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Abstract

The central problem in training a radial basis function neural network is the selection of hidden layer neurons, which includes the selection of the center and width of those neurons. In this paper, we propose to select hidden layer neurons based on multiple granularities immune network. Firstly a multiple granularities immune network (MGIN) algorithm is employed to reduce the data and get the candidate hidden neurons and construct an original RBF network including all candidate neurons. Secondly, the removing redundant neurons procedure is used to get a smaller network. Some experimental results show that the network obtained tends to generalize well.

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References

  1. Chen, S., Cowan, C.F., Grant, P.M.: Orthogonal Least Squares Learning Algorithms for Redial Basis Function Networks. IEEE Trans. Neural Networks 2(2), 302–309 (1991)

    Article  Google Scholar 

  2. Mao, K.Z., Huang, G.B.: Neuron Selection for RBF Neural Network Classifier Based on Data Structure Preserving Criterion. IEEE Trans. Neural Networks 16(6), 1531–1540 (2005)

    Article  Google Scholar 

  3. Huang, G.B., Saratchandran, P.: A Generalized Growing and Pruning RBF (GGAP-RBF) Neural Network for Function Approximation. IEEE Trans. Neural Networks 16(1), 57–67 (2005)

    Article  Google Scholar 

  4. Lee, S.J., Hou, C.L.: An ART-Based Construction of RBF Networks. IEEE Trans. Neural Networks 13(6), 1308–1321 (2002)

    Article  Google Scholar 

  5. Lee, H.M., Chen, C.M.: A Self-Organizing HCMAC Neural-Network Classifier. IEEE Trans. Neural Networks 14(1), 15–27 (2003)

    Article  Google Scholar 

  6. Miller, D., Rao, A.V.: A Global Optimization Technique for Statistical Classifier Design. IEEE Trans. on Signal Processing 44(12), 3108–3122 (1996)

    Article  Google Scholar 

  7. Timmis, J., Neal, M., Hunt, J.: An Artificial Immune System for Data Analysis. Biosystems 55(1), 143–150 (2000)

    Article  Google Scholar 

  8. Zhong, J., Wu, Z.F.: A Novel Dynamic Clustering Algorithm Based on Immune Network and Tabu Search. Chinese Journal of Electronics 14(2), 285–288 (2005)

    Article  MathSciNet  Google Scholar 

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Author information

Authors and Affiliations

  1. College of Computer Science and Technology, Chongqing University, Chongqing, 400044, China

    Jiang Zhong, Chun Xiao Ye, Yong Feng, Ying Zhou & Zhong Fu Wu

Authors
  1. Jiang Zhong
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  2. Chun Xiao Ye
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  3. Yong Feng
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  4. Ying Zhou
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  5. Zhong Fu Wu
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Editor information

Editors and Affiliations

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

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd., 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Cite this paper

Zhong, J., Ye, C.X., Feng, Y., Zhou, Y., Wu, Z.F. (2006). Neuron Selection for RBF Neural Network Classifier Based on Multiple Granularities Immune Network. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3971. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11759966_127

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  • DOI: https://doi.org/10.1007/11759966_127

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34439-1

  • Online ISBN: 978-3-540-34440-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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