Movatterモバイル変換


[0]ホーム

URL:


Skip to main content

Advertisement

Springer Nature Link
Log in

Evolved Bat Algorithm with Increase-Wave Strategy

  • Conference paper
  • First Online:

Part of the book series:Advances in Intelligent Systems and Computing ((AISC,volume 387))

  • 1060Accesses

Abstract

In this paper, a mixture signal, which is composed of a periodical signal and an increasing level Direct Current (DC) signal, is used in this paper to amplify the diversity brought to the artificial agents in Evolved Bat Algorithm (EBA). In order to test the accuracy on finding the near best solutions, three test functions with known global optimum are used in the experiments. The experimental results indicate that our method improves the searching accuracy of EBA about 47.74 percent in average.

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

Access this chapter

Subscribe and save

Springer+ Basic
¥17,985 /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
JPY 3498
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
JPY 17159
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
JPY 21449
Price includes VAT (Japan)
  • 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Tsai, P.-W., Pan, J.-S., Liao, B.-Y., Tsai, M.-J., Vaci, I.: Bat Algorithm Inspired Algorithm for Solving Numerical Optimization Problems. Applied Mechanics and Materials148–149, 134–137 (2012)

    Google Scholar 

  2. Yang, X.-S.: A new metaheuristic bat-inspired algorithm. In: González, J.R., Pelta, D.A., Cruz, C., Terrazas, G., Krasnogor, N. (eds.) NICSO 2010. SCI, vol. 284, pp. 65–74. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  3. Tsai, P.-W., Chen, C.-W.: A Novel Criterion for Nonlinear Time-Delay Systems Using LMI Fuzzy Lyapunov Method. Applied Soft Computing25, 461–472 (2014)

    Article MathSciNet  Google Scholar 

  4. Hasançebi, O., Teke, T., Pekcan, O.: A bat-inspired algorithm for structural optimization. Computers and Structures128, 77–90 (2013)

    Article MATH  Google Scholar 

  5. Niknam, T., Azizipanah-Abarghooee, R., Zare, M., Bahmani-Firouzi, B.: Reserve Constrained Dynamic Environmental/Economic Dispatch: A New Multiobjective Self-Adaptive Learning Bat Algorithm. IEEE Systems Journal7(4), 763–776 (2013)

    Article MATH  Google Scholar 

  6. Tsai, P.-W., Pan, J.-S., Liao, B.-Y., Chu, S.-C.: Ehanced Artificial Bee Colony Optimization. International Journal of Innovative Computing Information and Control5(12(B)), 5081–5092 (2009)

    Google Scholar 

  7. Tsai, P.-W., Khan, M.K., Pan, J.-S., Liao, B.-Y.: Interactive Artificial Bee Colony Supported Passive Continuous Authentication System. IEEE Systems JournalPP, 1–11 (2012)

    MATH  Google Scholar 

  8. Chu, S.-C., Tsai, P.-W.: Computational Intelligence Based on the Behavior of Cats. International Journal of Innovative Computing, Information and Control3(1), 163–173 (2007)

    Google Scholar 

  9. Chu, S.-C., Tsai, P.-w., Pan, J.-S.: Cat swarm optimization. In: Yang, Q., Webb, G. (eds.) PRICAI 2006. LNCS (LNAI), vol. 4099, pp. 854–858. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  10. Tsai, P.-W., Pan, J.-S., Chen, S.-M., Liao, B.-Y.: Enhanced Parallel Cat Swarm Optimization Based on the Taguchi Method. Expert Systems with Applications39(7), 6309–6319 (2012)

    Article  Google Scholar 

  11. Temel, S., Unaldi, N., Kaynak, O.: On Deployment of Wireless Sensors on 3-D Terrains to Maximize Sensing Coverage by Utilizing Cat Swarm Optimization with Wavelet Transform. IEEE Transactions on Systems, Man, and Cybernetics: Systems44(1), 111–120 (2014)

    Article MATH  Google Scholar 

  12. Kong, L., Pan, J.-S., Tsai, P.-W., Vaclav, S., Ho, J.-H.: A Balanced Power Consumption Algorithm Based on Enhanced Parallel Cat Swarm Optimization for Wireless Sensor Network. International Journal of Distributed Sensor Networks2015, 1–10 (2015)

    Article  Google Scholar 

  13. Pappula, L., Ghosh, D.: Linear antenna array synthesis using cat swarm optimization. International Journal of Electronics and Communications (AEÜ)68, 540–549 (2014)

    Article MATH  Google Scholar 

  14. Yang, F., Ding, M., Zhang, X., Hou, W., Zhong, C.: Non-rigid multi-modal medical image registration by combining L-BFGS-B with cat swarm optimization. Information Sciences (in press) (2015)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Information Science and Engineering, Fujian University of Technology, Fuzhou City, 350118, Fujian, China

    Pei-Wei Tsai, Shunmiao Zhang, Yuan Liu, Yao He & Jeng-Shyang Pan

  2. Innovative Information Industry Research Center, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, 518055, China

    Jeng-Shyang Pan

Authors
  1. Pei-Wei Tsai

    You can also search for this author inPubMed Google Scholar

  2. Shunmiao Zhang

    You can also search for this author inPubMed Google Scholar

  3. Yuan Liu

    You can also search for this author inPubMed Google Scholar

  4. Yao He

    You can also search for this author inPubMed Google Scholar

  5. Jeng-Shyang Pan

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence toJeng-Shyang Pan.

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Miyazaki, Miyazaki, Japan

    Thi Thi Zin

  2. School of Computer Science and Tech..., Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China

    Jerry Chun-Wei Lin

  3. College of Information Science and Engg, Fujian University of Technology, Fuzhou, China

    Jeng-Shyang Pan

  4. Faculty of Engineering, University of Miyazaki, Miyazaki, Japan

    Pyke Tin

  5. Faculty of Engineering, University of Miyazaki, Miyazaki, Japan

    Mitsuhiro Yokota

Rights and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Tsai, PW., Zhang, S., Liu, Y., He, Y., Pan, JS. (2016). Evolved Bat Algorithm with Increase-Wave Strategy. In: Zin, T., Lin, JW., Pan, JS., Tin, P., Yokota, M. (eds) Genetic and Evolutionary Computing. Advances in Intelligent Systems and Computing, vol 387. Springer, Cham. https://doi.org/10.1007/978-3-319-23204-1_3

Download citation

Publish with us

Access this chapter

Subscribe and save

Springer+ Basic
¥17,985 /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
JPY 3498
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
JPY 17159
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
JPY 21449
Price includes VAT (Japan)
  • 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


[8]ページ先頭

©2009-2025 Movatter.jp