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Optimization of Neural Tree Based on Good Point Set

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Intelligent Computing Theories and Application (ICIC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10361))

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Abstract

Particle swarm optimization algorithm is often used in the optimization of parameters in the model of flexible neural tree. Using the principle of good point set in number theory, a novel algorithm of creating good point is presented to modify initial population setting, which is combined with the disturbance, so as to be used to overcome the shortcomings of particle swarm optimization algorithm, such as being slow, easily trapped in local optimal solution. In this paper, flexible neural tree, using hyperbolic tangent as transfer function, with the novel particle swarm optimization algorithm is applied to provide a reliable and effective forecast framework for stock market indices. The Nasdaq-100 index of Nasdaq Stock Market and the S&P CNX NIFTY stock index are analyzed. Several years of Nasdaq 100 main-index values and NIFTY index values are considered using several intelligent computing techniques. The result shows that the proposed algorithm could represent the stock indices behavior very accurately.

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Acknowledgements

The research work was supported by National Natural Science Foundation of China under Grant No. 60573065.

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Authors and Affiliations

  1. School of Information Science and Engineering, University of Jinan, Jinan, 250022, China

    Hao Teng & Shixian Wang

  2. Shandong Provincial Key Laboratory of Network Based Intelligent Computing, Jinan, 250022, China

    Yuehui Chen

Authors
  1. Hao Teng
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  2. Yuehui Chen
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  3. Shixian Wang
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Corresponding author

Correspondence to Hao Teng .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. Politecnico di Bari, Bari, Italy

    Vitoantonio Bevilacqua

  3. University of Wollongong, North Wollongong, New South Wales, Australia

    Prashan Premaratne

  4. Indian Institute of Technology, Kanpur, India

    Phalguni Gupta

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Teng, H., Chen, Y., Wang, S. (2017). Optimization of Neural Tree Based on Good Point Set. In: Huang, DS., Bevilacqua, V., Premaratne, P., Gupta, P. (eds) Intelligent Computing Theories and Application. ICIC 2017. Lecture Notes in Computer Science(), vol 10361. Springer, Cham. https://doi.org/10.1007/978-3-319-63309-1_69

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  • DOI: https://doi.org/10.1007/978-3-319-63309-1_69

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63308-4

  • Online ISBN: 978-3-319-63309-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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