Advertisement

The Pattern Classification Based on Fuzzy Min-max Neural Network with New Algorithm

  • Dazhong Ma
  • Jinhai Liu
  • Zhanshan Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7368)

Abstract

A new fuzzy min-max neural network (FMNN) based on based on new algorithm is proposed for pattern classification. A new membership function of hyperbox is defined in which the characteristic are considered. The FMNN with new learning algorithm don’t use contraction process of fuzzy min-max neural network described by Simpson.The new algorithm only need expansion and no additional neurons have been added to the neural network to deal with the overlapped area. FMNN with new algorithm has strong robustness and high accuracy in classification for considering the characteristic of data core and noise. The performance of FMNN with new algorithm is checked by some benchmark data sets and compared with some traditional methods. All the results indicate that FMNN with new algorithm is effective. abstract environment.

Keywords

fuzzy min-max neural network patter classification robustness learning algorithm 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Ou, G.B., Murphey, Y.L.: Multi-class pattern classification using neural networks. Pattern Recognition 40(1), 4–18 (2007)zbMATHCrossRefGoogle Scholar
  2. 2.
    Parekh, R., Yang, J., Honavar, V.: Constructive neural-network learning algorithms for pattern classification. IEEE Trans. Neural Networks 11(2), 436–451 (2000)CrossRefGoogle Scholar
  3. 3.
    Benitez, J.M., Castro, J.L., Requena, T.: Are artificial neural networks black boxes. IEEE Trans. Neural Networks 8(5), 1156–1164 (1997)CrossRefGoogle Scholar
  4. 4.
    Ozbay, Y., Ceylan, R., Karlik, B.: A fuzzy clustering neural network architecture for classification of ECG arrhythmias. Computers in Biology and Medicine 36(4), 376–388 (2006)CrossRefGoogle Scholar
  5. 5.
    Li, R.P., Mukaidono, M., Turksen, I.B.: A fuzzy neural network for pattern classification and feature selection. Fuzzy Sets and Systems 130(1), 101–108 (2002)MathSciNetzbMATHCrossRefGoogle Scholar
  6. 6.
    Juang, C.F., Tsao, Y.W.: A Self-Evolving Interval Type-2 Fuzzy Neural Network With Online Structure and Parameter Learning. IEEE Trans. Fuzzy Systems 16(6), 1411–1424 (2008)CrossRefGoogle Scholar
  7. 7.
    Tagliaferri, R., Eleuteri, A., Meneganti, M., Barone, F.: Fuzzy Min-Max neural networks: from classification to regression. Soft Computation 5(6), 69–76 (2001)zbMATHCrossRefGoogle Scholar
  8. 8.
    Simpson, P.K.: Fuzzy Min-Max neural networks-PartI: Classification. IEEE Trans. Neural Networks 3(5), 776–786 (1992)CrossRefGoogle Scholar
  9. 9.
    Simpson, P.K.: Fuzzy Min-Max neural network-Part II: Clustering. IEEE Trans. Fuzzy Systems 1(1), 32–45 (1993)CrossRefGoogle Scholar
  10. 10.
    Alpern, B., Carter, L.: The hyperbox. In: Proc. IEEE Conf. Visualization, pp. 133–139 (October 1991)Google Scholar
  11. 11.
    Rizzi, A., Panella, M., Mascioli, F.M.F.: A recursive algorithm for fuzzy min-max networks. In: Proc. IEEE/INNS/ENNS. International Joint Conference Neural Networks (IJCNN 2000), vol. 6, pp. 541–546 (July 2000)Google Scholar
  12. 12.
    Gabrys, B., Bargiela, A.: General fuzzy Min-Max neural network for clustering and classification. IEEE Trans. Neural Networks 11(3), 769–783 (2000)CrossRefGoogle Scholar
  13. 13.
    Quteishat, A., Lim, C.P.: A modified fuzzy Min-Max neural network with rule extraction and its application. Applied Soft Computing 8(2), 985–995 (2008)CrossRefGoogle Scholar
  14. 14.
    Quteishat, A., Lim, C.P., Tan, K.S.: A modified fuzzy Min-Max neural network with a genetic-algorithm-based rule extractor pattern classification. IEEE Trans. System, Man, and Cybernetics-Part A: Systems and Humans 40(3), 641–650 (2010)CrossRefGoogle Scholar
  15. 15.
    Nandedkar, A.V., Biswas, P.K.: A fuzzy min-max neural network classifier with compensatory neuron architecture. IEEE Trans. Neural Networks 18(1), 42–54 (2007)CrossRefGoogle Scholar
  16. 16.
    Zhang, H.G., Liu, J.H., Ma, D.Z., Wang, Z.S.: Data-Core-Based Fuzzy Min-Max Neural Network for Pattern Classification. IEEE Trans. Neural Networks 22(12), 2339–2352 (2011)CrossRefGoogle Scholar
  17. 17.
    Blake, C., Keogh, E., Merz, C.J.: UCI Repository of Machine Learning Database University of California, Irvine (1998), http://www.ics.uci.edu/~mlearn/MLRepositroy.html

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Dazhong Ma
    • 1
  • Jinhai Liu
    • 1
  • Zhanshan Wang
    • 1
  1. 1.College of Information Science and EngineeringNortheastern UniversityShenyangChina

Personalised recommendations