Skip to main content
SpringerLink
Log in
Book cover

International Conference on Applied Informatics and Communication

ICAIC 2011: Applied Informatics and Communication pp 10–17Cite as

Inversion of TEM Conductive Thin Layer Based on Genetic Algorithm

  • Conference paper

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 226))

Abstract

Using the adaptive shrinkage genetic algorithm in the feasible region to operate the inversion of TEM (transient electromagnetic method) conductive thin layer with the apparent vertical conductance differential imaging. In contrast, this inversion method accelerates the calculation speed and improves the calculation precision. Meanwhile, we utilize the genetic algorithm to derive the conductive imaging parameter and realize the global non-linear inversion compared to traditional method in local scope.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Wang, X., Cao, L.: The Genetic Algorithm –Thoery, Application and The Simulated Software. Xi’an Jiaotong University publishhouse (2002)

    Google Scholar 

  2. Liu, Y., Cao, C.: Inversion of one 2dimensional MT data using genetic algorithms. Journal of Zhejiang University (Natural Science) 31(3), 300–305 (1997)

    Google Scholar 

  3. Wei, G., Hu, W.: MT Data Inversion. Journal of Jianghan Petroleum Institute 21(3), 25–29 (1999)

    Google Scholar 

  4. Zhang, X.: Transient electromagnetic local conductor inversion by genetic algorithm. Guilin Institute of Technology 22(4), 454–457 (2002)

    Google Scholar 

  5. Chen, J., Wang, J., et al.: Application Of Improved Genetic Algorithm To Inversion Of Multi-Layer Density Interface. Earth Science —Journal of China University of Geosciences 25(6), 651–654 (2000)

    Google Scholar 

  6. Li, X.: The theory and Application of Transient Electromagnetic Sounding. Shanxi Science Publishhouse (2002)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, 710049, China

    Guo Wenbo

  2. Institute of Geology and Geophysics, Beijing, 100029, China

    Xue Guoqiang & Zhou Nannan

  3. Chang’an University, Xi’an, 710054, China

    Li Xiu

Authors
  1. Guo Wenbo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xue Guoqiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhou Nannan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Li Xiu
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Suzhou University, No. 50 Donghuan Road, 215021, China

    Jianwei Zhang

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Wenbo, G., Guoqiang, X., Nannan, Z., Xiu, L. (2011). Inversion of TEM Conductive Thin Layer Based on Genetic Algorithm. In: Zhang, J. (eds) Applied Informatics and Communication. ICAIC 2011. Communications in Computer and Information Science, vol 226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23235-0_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-23235-0_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23234-3

  • Online ISBN: 978-3-642-23235-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation