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Application of Genetic Algorithm to Hausdorff Measure Estimation of Sierpinski Carpet

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4693))

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Abstract

In this paper, we discuss the realization of the genetic algorithm on calculating the Hausdorff measure of the Sierpinski gasket with compression ratio 1/2 in detail, mainly including the encoding and decoding method, generation of the initial population, and fitness computation. The experimental results prove that the genetic algorithm is an effective and universal method to calculate Hausdorff measure.

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References

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Author information

Authors and Affiliations

  1. School of Computer Science and Information Technology, Zhejiang Wanli University, Ningbo, Zhejiang, 315100, P.R. China

    Qili Xiao & Lifeng Xi

Authors
  1. Qili Xiao
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  2. Lifeng Xi
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Editor information

Editors and Affiliations

  1. Dipartimento di Scienze dell’Informazione, Università degli Studi di Milano, Via Comelico 39/41, 20135, Milano, Italy

    Bruno Apolloni

  2. Centre for SMART Systems, School of Engineering, University of Brighton, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. Knowledge-Based Intelligent Engineering Systems Centre, University of South Australia, Mawson Lakes, SA 5095, Adelaide, Australia

    Lakhmi Jain

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© 2007 Springer-Verlag Berlin Heidelberg

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Xiao, Q., Xi, L. (2007). Application of Genetic Algorithm to Hausdorff Measure Estimation of Sierpinski Carpet. In: Apolloni, B., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2007. Lecture Notes in Computer Science(), vol 4693. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74827-4_23

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  • DOI: https://doi.org/10.1007/978-3-540-74827-4_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74826-7

  • Online ISBN: 978-3-540-74827-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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