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Adaptive Immune Response Network Model

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Emerging Intelligent Computing Technology and Applications. With Aspects of Artificial Intelligence (ICIC 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5755))

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Abstract

Artificial immune system (AIS) and its applications have become a search hotspot in recent years. According to the theory of immune response and immune network, the Adaptive Immune Response Network (AIRN) is presented in this paper. In AIRN, the expression and procedure are given. The AIRN is applied to the clustering analysis, and this cluster method can receive data modes more quickly. The testing results show that the AIRN has better performance in data partition and pattern recognition than the clustering algorithm based on GA and the others.

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Author information

Authors and Affiliations

  1. JiangSu Province Support Software Engineering R&D Center for Modern Information Technology Application in Enterprise, Suzhou, 215104, Jiangsu, China

    Tao Liu

  2. Department of Electronics & Information Engineering, Suzhou Vocational University, Email: banklt@163.com, Suzhou, 215104, Jiangsu, China

    Tao Liu, Li Zhang & Binbin Shi

Authors
  1. Tao Liu
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  2. Li Zhang
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  3. Binbin Shi
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Editor information

Editors and Affiliations

  1. Institute of Intelligent Machines, Chinese Academy of Sciences, China

    De-Shuang Huang

  2. Graduate School of Electrical Engineering, University of Ulsan, Korea, San 29, Mugeo-Dong, Nam-Ku, 680 - 749, Ulsan, Korea

    Kang-Hyun Jo

  3. School of Electrical Engineering, University of Ulsan, Ulsan, South Korea

    Hong-Hee Lee

  4. School of Electrical Engineering, University of Ulsan, South Korea

    Hee-Jun Kang

  5. e.B.I.S. s.r.l. (electronic Business in Security), Spin-Off of Polytechnic of Bari, Str. Prov. per Casamassima Km., 3, 70010, Valenzano, (BA), Italy

    Vitoantonio Bevilacqua

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© 2009 Springer-Verlag Berlin Heidelberg

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Liu, T., Zhang, L., Shi, B. (2009). Adaptive Immune Response Network Model. In: Huang, DS., Jo, KH., Lee, HH., Kang, HJ., Bevilacqua, V. (eds) Emerging Intelligent Computing Technology and Applications. With Aspects of Artificial Intelligence. ICIC 2009. Lecture Notes in Computer Science(), vol 5755. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04020-7_96

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  • DOI: https://doi.org/10.1007/978-3-642-04020-7_96

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04019-1

  • Online ISBN: 978-3-642-04020-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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