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Evolved Bat Algorithm with Increase-Wave Strategy

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Genetic and Evolutionary Computing

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

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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.

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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
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  2. Shunmiao Zhang
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  3. Yuan Liu
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  4. Yao He
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  5. Jeng-Shyang Pan
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Corresponding author

Correspondence to Jeng-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

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© 2016 Springer International Publishing Switzerland

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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

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  • DOI: https://doi.org/10.1007/978-3-319-23204-1_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23203-4

  • Online ISBN: 978-3-319-23204-1

  • eBook Packages: EngineeringEngineering (R0)

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