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International Symposium on Neural Networks

ISNN 2007: Advances in Neural Networks – ISNN 2007 pp 151–159Cite as

A Fuzzy Neural Network Based on Back-Propagation

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4492))

Abstract

Some arguments on fuzzy neural network algorithm have been put forward, whose weights were considered as special fuzzy numbers. This paper proposes a conception of strong L-R type fuzzy number and derives a learning algorithm based on BP algorithm via level sets of strong L-R type fuzzy numbers. The special fuzzy number has been weakened to the common case. Then the range of application has been enlarged.

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References

  1. Liu, M., Quan, T., Luan, S.: An Attribute Recognition System Based on Rough Set Theory-Fuzzy Neural Network and Fuzzy Expert System. In: Fifth World Congress on Intelligent Control and Automation (WCICA), pp. 2355–2359 (2004)

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  2. Wang, S.-Q., Li, Z.-H., Xiao, Z.-H., Zhang, Z.-P.: Application of GA-FNN Hybrid Control System for Hydroelectric Generating Units. In: Proc. Int. Conf. Machine Learning and Cybernetics, vol. 2, pp. 840–845 (2005)

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  3. Dubois, D., Prade, H.: Fuzzy Sets and Systems-Theory and Applications. Academic Press, New York (1982)

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  4. Feng, L., Liu, Z.Y.: Genetic Algorithms and Rough Fuzzy Neural Network-based Hybrid Approach for Short-term Load Forecasting. In: IEEE: Power Engineering Society General Meeting, pp. 1–6 (2006)

    Google Scholar 

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Author information

Authors and Affiliations

  1. NanJing Artillery Academy, NanJing 211132,  

    Huang Jin, Gan Quan & Cai Linhui

  2. NanJing University of Science and Technology, NanJing 210094,  

    Huang Jin

Authors
  1. Huang Jin
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  2. Gan Quan
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  3. Cai Linhui
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Editor information

Derong Liu Shumin Fei Zengguang Hou Huaguang Zhang Changyin Sun

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© 2007 Springer Berlin Heidelberg

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Cite this paper

Jin, H., Quan, G., Linhui, C. (2007). A Fuzzy Neural Network Based on Back-Propagation. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72393-6_20

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  • DOI: https://doi.org/10.1007/978-3-540-72393-6_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72392-9

  • Online ISBN: 978-3-540-72393-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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