DOI QR코드

DOI QR Code

Design of Hard Partition-based Non-Fuzzy Neural Networks

  • Park, Keon-Jun (Dept. of Information and Communication Engineering, Wonkwang University) ;
  • Kwon, Jae-Hyun (Dept. of Information and Communication Engineering, Wonkwang University) ;
  • Kim, Yong-Kab (Dept. of Information and Communication Engineering, Wonkwang University)
  • Received : 2012.09.03
  • Published : 2012.11.30

Abstract

This paper propose a new design of fuzzy neural networks based on hard partition to generate the rules of the networks. For this we use hard c-means (HCM) clustering algorithm. The premise part of the rules of the proposed networks is realized with the aid of the hard partition of input space generated by HCM clustering algorithm. The consequence part of the rule is represented by polynomial functions. And the coefficients of the polynomial functions are learned by BP algorithm. The number of the hard partition of input space equals the number of clusters and the individual partitioned spaces indicate the rules of the networks. Due to these characteristics, we may alleviate the problem of the curse of dimensionality. The proposed networks are evaluated with the use of numerical experimentation.

Keywords

Non-Fuzzy Neural Networks;Hard partition;HCM clustering;Scatter partition;Rule Generation

References

  1. T. Yamakawa, "A Neo Fuzzy Neuron and Its Application to System Identification and Prediction of the System Behavior," Proceeding of the 2nd International Conference on Fuzzy logic & Neural Networks, pp. 17-22, 1992.
  2. J. J. Buckley and Y. Hayashi, "Fuzzy neural networks: A survey," Fuzzy Sets Syst. Vol. 66, 1994.
  3. J.S.R. Jang, E. Mizutani, and C.T. Sun, Neuro-Fuzzy and Soft Computing, A Computational Approach to Learning and Machine Intelligence, Prentice Hall, NJ, 1997.
  4. J. J. Park, G. S. Choi, and I.-S. Ahn, "Multi-variable Fuzzy Modeling for Combustion Control of Refuse Incineration Plant," Journal of the Institute of Webcasting, Internet and Telecommunication(IWIT), Vol. 9, No. 5, pp. 191-197, 2009.
  5. T. A. Tuan and I. S. Koo, "A Channel Selection Algorithm Based on Fuzzy Logic and Learning Automata for Cognitive Radio Sensor Networks", Journal of the Institute of Webcasting, Internet and Telecommunication(IWIT), Vol. 11. No. 1, pp. 23-28, 2011.
  6. I. K. Park, " A Study on the Prediction of the Nonlinear Chaotic Time Series Using Genetic Algorithm based Fuzzy Neural Network", Journal of the Institute of Webcasting, Internet and Telecommunication(IWIT), Vol. 11. No. 4, pp. 91-97, 2011.
  7. P. R. Krishnaiah and L. N. Kanal, editors. Classification, pattern recognition, and reduction of dimensionality, volume 2 of Handbook of Statistics. North-Holland, Amsterdam, 1982.
  8. G. E. P. Box and G. M. Jenkins, Time Series Analysis, Forecasting, and Control, 2nd edition Holden-Day, SanFransisco, 1976.