[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to main content
Springer Nature Link
Log in

Convergence Analysis of Self-adaptive Immune Particle Swarm Optimization Algorithm

  • Conference paper
  • First Online:
Advances in Neural Networks – ISNN 2018 (ISNN 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10878))

Included in the following conference series:

Abstract

The self-adaptive immune particle swarm optimization (SAIPSO) algorithm is a hybrid algorithm based on immune algorithm and particle swarm optimization algorithm. SAIPSO algorithm has been implemented and achieved better result compared with the classical particle swarm optimization algorithm. However, the theoretical support of the algorithm is equally important as the implementation of the algorithm. Therefore, this paper mainly uses the convergence theorem of random search algorithm and the mathematical induction to prove the convergence of SAIPSO algorithm, which will help the improvement and application of the algorithm in the future.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
GBP 19.95
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
GBP 71.50
Price includes VAT (United Kingdom)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
GBP 89.99
Price includes VAT (United Kingdom)
  • 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

Institutional subscriptions

Similar content being viewed by others

References

  1. Solis, F., Wets, R.: Minimization by random search techniques. Math. Oper. Res. 6, 19–30 (1981)

    Article  MathSciNet  Google Scholar 

  2. Tang, F., Li, M., Luo, A.: Global convergence analysis of an artificial immune algorithm. J. Changsha Univ. Electr. Pow. 19, 1–4 (2004)

    Google Scholar 

  3. Cui, H., Zhu, Q.: Convergence analysis and parameter selection in particle swarm optimization. Comput. Eng. Appl. 43, 89–91 (2007)

    Google Scholar 

  4. Zhang, H., Wang, H., Zhijun, H.: Analysis of particle swarm optimization algorithm global convergence method. Eng. Appl. 47, 61–63 (2011)

    Google Scholar 

  5. Han, L.: The study of immune particle swarm optimization algorithm and its application. Xi’an Polytechnic University (2008)

    Google Scholar 

  6. Zhang, C., Li, Q.: Immune particle swarm optimization algorithm based on the adaptive search strategy. Chin. J. Eng. 39, 125–132 (2017)

    Google Scholar 

  7. Sun, L., Hailang, X., Ge, H.: Novel global convergence stochastic particle swarm optimization optimizers. J. Jilin Univ. 47, 615–621 (2017)

    Google Scholar 

  8. Xie, Z., Zhong, S., Wei, Y.: Modified particle swarm optimization algorithm and its convergence analysis. Comput. Eng. Appl. 47, 46–49 (2011)

    Google Scholar 

Download references

Acknowledgement

This work was supported by The National Natural Science Foundation of China (Project No. 61662057, 61672301) and Higher Educational Scientific Research Projects of Inner Mongolia Autonomous Region (Project No. NJZC17198).

Author information

Authors and Affiliations

  1. College of Computer Science and Technology, Inner Mongolia University for Nationalities, Tongliao, 028043, China

    Jingqing Jiang & Chenggang Zhang

  2. College of Mathematics, Inner Mongolia University for Nationalities, Tongliao, 028043, China

    Jingqing Jiang, Chuyi Song & Huan Ping

Authors
  1. Jingqing Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chuyi Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Huan Ping
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chenggang Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Huan Ping .

Editor information

Editors and Affiliations

  1. Texas A&M University at Qatar, Doha, Qatar

    Tingwen Huang

  2. Sichuan University, Chengdu, China

    Jiancheng Lv

  3. Southeast University, Nanjing, China

    Changyin Sun

  4. United Institute of Informatics Problems, Minsk, Belarus

    Alexander V. Tuzikov

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Jiang, J., Song, C., Ping, H., Zhang, C. (2018). Convergence Analysis of Self-adaptive Immune Particle Swarm Optimization Algorithm. In: Huang, T., Lv, J., Sun, C., Tuzikov, A. (eds) Advances in Neural Networks – ISNN 2018. ISNN 2018. Lecture Notes in Computer Science(), vol 10878. Springer, Cham. https://doi.org/10.1007/978-3-319-92537-0_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-92537-0_19

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92536-3

  • Online ISBN: 978-3-319-92537-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation