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An Improved Relative Criterion Using BP Algorithm

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Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3496))

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Abstract

People are usually more interested in ranking a group of interrelated objects than the actual scores of them. In this paper, we presented an improved relative evaluation criterion, which is suitable for such task and can solve those problems that are difficult to deal with by common absolute criterion. We put forward the improvement algorithm and realize its function approximation by means of BP algorithm. Furthermore, we tested this criterion with the statistic data of SARS. The experimental results indicated that our improved criterion is effective in comparing a set of correlative objects objectively. Finally, we made a conclusion about the goal and efficiency of relative criterion.

This research was supported by NSFC (No.60435010), NSFB (No.4052025) and National Great Basic Research Program (973 project No.2003CB317000)

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References

  1. Liu, J.: The Theory Research of Relative Criterion Method in Scatter Quantity System. In: Proceedings of Join Faculty of Computer Scientific Research, ICT&CNU, pp. 14–18 (2004)

    Google Scholar 

  2. Hornik, K., Stinchcombe, M., White, H.: Multilayer Feedforward Networks Are Universal Approximators. Neural Networks 2, 359–366 (1989)

    Article  Google Scholar 

  3. Hagan, M.T., et al.: Neural Network Design. PWS Publishing Company (1995)

    Google Scholar 

  4. Yuan, C.: Artificial Neural Networks and Applications. Tsinghua University (1999)

    Google Scholar 

  5. http://www.mathworks.com/access/helpdesk/help/techdoc/matlab.html

  6. http://big5.china.com.cn/english/jianghua/72566.htm

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Author information

Authors and Affiliations

  1. Institute of Computing and Technology, Chinese Academy of Sciences, Beijing, 100080, China

    Zhiyong Zhang & Zhongzhi Shi

  2. Graduate School of the Chinese Academy of Sciences, Beijin, 100039, China

    Zhiyong Zhang

  3. Join Faculty of Computer Scientific Research, Capital Normal University, Beijing, 100037, China

    Jingang Liu

Authors
  1. Zhiyong Zhang
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  2. Jingang Liu
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  3. Zhongzhi Shi
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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. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiaofeng Liao

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

    Zhang Yi

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© 2005 Springer-Verlag Berlin Heidelberg

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Zhang, Z., Liu, J., Shi, Z. (2005). An Improved Relative Criterion Using BP Algorithm. In: Wang, J., Liao, X., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427391_94

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  • DOI: https://doi.org/10.1007/11427391_94

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25912-1

  • Online ISBN: 978-3-540-32065-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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