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Optimal Search Plan Model for Lost Aircraft

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Data Science (ICDS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9208))

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Abstract

In this passage, we intend to determinate the specific searching plan for lost aircraft on the basis of big data application. First, it uses the Neural Network Model to solve the problem about area classification by means of SOM. Then, we cope with Maximum Flow Problem by BFS, in order to the determination of cruise route.

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Notes

  1. 1.

    http://en.wikipedia.org/wiki/Self-organizing_map.

  2. 2.

    http://en.wikipedia.org/wiki/Maximum_flow_problem#cite_note-9.

Reference

  1. Kohonen, T., Honkela, T.: Kohonen network. Scholarpedia (2011). Retrieved 2012-09-24

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Author information

Authors and Affiliations

  1. China University of Political Science and Law, No. 27, Fuxue Street, Changping District, Beijing, China

    Luyao Zhu & Wenxi Hao

  2. Tianjin Polytechnic University, No. 399, Binshuixi Road, Tianjin, China

    Zhiwei Zhu

Authors
  1. Luyao Zhu
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  2. Wenxi Hao
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  3. Zhiwei Zhu
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Corresponding authors

Correspondence to Luyao Zhu , Wenxi Hao or Zhiwei Zhu .

Editor information

Editors and Affiliations

  1. University of Technology, Sydney, Australia

    Chengqi Zhang

  2. Xi'an Jiaotong University, Xi'an Jiaotong, China

    Wei Huang

  3. Chinese Academy of Sciences, Beijing, China

    Yong Shi

  4. University of Illinois Chicago, CHICAGO, Illinois, USA

    Philip S. Yu

  5. Fudan University, Shanghai, China

    Yangyong Zhu

  6. Research Center on Fictitious Econo, Chinese Academy of Sciences, Beijing, China

    Yingjie Tian

  7. University of Technology, Sydney, Australia

    Peng Zhang

  8. Victoria University, Melbourne, Victoria, Australia

    Jing He

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Appendix

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© 2015 Springer International Publishing Switzerland

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Cite this paper

Zhu, L., Hao, W., Zhu, Z. (2015). Optimal Search Plan Model for Lost Aircraft. In: Zhang, C., et al. Data Science. ICDS 2015. Lecture Notes in Computer Science(), vol 9208. Springer, Cham. https://doi.org/10.1007/978-3-319-24474-7_23

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  • DOI: https://doi.org/10.1007/978-3-319-24474-7_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24473-0

  • Online ISBN: 978-3-319-24474-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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