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Improving the Searching Capacity of Evolved Bat Algorithm by the Periodic Signal

  • Pei-Wei Tsai
  • Sijing Cai
  • Vaci Istanda
  • Lyu-Chao Liao
  • Jeng-Shyang Pan
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 387)

Abstract

In this paper, the evolved bat algorithm is improved by replacing the fixed value, which is determined by the media, with the periodic signal. The familiar periodic signal exists in the natural environment is the sine/cosine signal. We take the cosine signal in our design of improving the searching capacity of the evolved bat algorithm. Three test functions, of which the global optimum values are known, are used in the experiments. The experimental results indicate that our proposed strategy improves the searching accuracy of the evolved bat algorithm about 45.722% in average.

Keywords

Evolved bat algorithm Swarm intelligence Periodic signal Optimization 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Pei-Wei Tsai
    • 1
    • 2
  • Sijing Cai
    • 1
  • Vaci Istanda
    • 3
  • Lyu-Chao Liao
    • 2
  • Jeng-Shyang Pan
    • 1
    • 4
  1. 1.College of Information Science and EngineeringFujian University of TechnologyFuzhou CityChina
  2. 2.Key Laboratory for Automotive Electronics and Electric Drive of Fujian ProvinceFujian University of TechnologyFuzhou CityChina
  3. 3.Council of Indigenous PeoplesExecutive YuanNew Taipei CityTaiwan
  4. 4.Innovative Information Industry Research Center, Shenzhen Graduate SchoolHarbin Institute of TechnologyShenzhenChina

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