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An Improved Quantum Genetic Algorithm and Its Application

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Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2639))

Abstract

An improved quantum genetic algorithm (IQGA) is proposed in this paper. In IQGA, the strategies of updating quantum gate by using the best solution and introducing population catastrope are used. The typical function tests show convergent speed of IQGA is faster than that of quantum genetic algorithm(QGA) and other several GAs, and IQGA can also make up for prematureness of QGA. The simulations of FIR filter design demonstrate IQGA is superior to QGA, the methods in reference [5] and traditional method.

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References

  1. Tony Hey, Quantum Computing: an introduction[J], Computing & Control Engineering Journal, June 1999, pp105–112

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  5. Cheng **, Yu Shenglin, FIR filter design: frequency sampling technique based on genetic algorithm [J], Journal of Nan**g University of Aeronautics & Astronautics, 2000, 32(3): pp276–281

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Author information

Authors and Affiliations

  1. School of Electrical Engineering, Southwest Jiaotong University, Sichuan, 610031, P.R.China

    Gexiang Zhang, Weidong ** & Na Li

Authors
  1. Gexiang Zhang
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  2. Weidong **
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  3. Na Li
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Editor information

Editors and Affiliations

  1. Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, P.R. China

    Guoyin Wang

  2. Department of Computer Science, Nanchang University, Nanchang, 330029, P.R. China

    Qing Liu

  3. Department of Computer Science, University of Regina, Regina, Saskatchewan, S4S 0A2, Canada

    Yiyu Yao

  4. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Andrzej Skowron

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© 2003 Springer-Verlag Berlin Heidelberg

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Zhang, G., **, W., Li, N. (2003). An Improved Quantum Genetic Algorithm and Its Application. In: Wang, G., Liu, Q., Yao, Y., Skowron, A. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2003. Lecture Notes in Computer Science(), vol 2639. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39205-X_75

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  • DOI: https://doi.org/10.1007/3-540-39205-X_75

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-14040-5

  • Online ISBN: 978-3-540-39205-7

  • eBook Packages: Springer Book Archive

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