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SAPSO Neural Network for Inspection of Non-development Hatching Eggs

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Advances in Natural Computation (ICNC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4221))

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Abstract

Detection fertility and development in hatchery eggs could increase efficiency in commercial hatcheries. A new algorithm named simulated annealing particle swarm optimization algorithm (SAPSO) is proposed, and it is used to optimize topology structure of multi-layer feedback forward neural network for classification of hatching eggs. Trained and tested by a great deal of samples, a reasonable neural network model is obtained. Its performance is measured in terms of two parameters: short computing time and accuracy in the classification process.

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References

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Author information

Authors and Affiliations

  1. College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Huhhot, 010018, China

    Yu Zhi-hong, Wang Chun-guang & Feng Jun-qing

Authors
  1. Yu Zhi-hong
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  2. Wang Chun-guang
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  3. Feng Jun-qing
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Editor information

Editors and Affiliations

  1. Life Science Research Center, School of Electronic Engineering, Xidian University, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  3. School of Electronic Engineering, Xidian Univ., 710071, Xi’an, P.R. China

    Xin-bo Gao

  4. College of Mathematics and Information Science, Hebei Normal University, 050016, Shijiazhuang, Hebei, P.R. China

    Jing Liu

  5. Multi-Agent Systems Lab,Department of Computer Science, University of Science and Technology of China, 230026, Hefei, China

    Feng Wu

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© 2006 Springer-Verlag Berlin Heidelberg

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Zhi-hong, Y., Chun-guang, W., Jun-qing, F. (2006). SAPSO Neural Network for Inspection of Non-development Hatching Eggs. In: Jiao, L., Wang, L., Gao, Xb., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4221. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881070_13

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  • DOI: https://doi.org/10.1007/11881070_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45901-9

  • Online ISBN: 978-3-540-45902-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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