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International Conference in Swarm Intelligence

ICSI 2011: Advances in Swarm Intelligence pp 408–415Cite as

A Modified Artificial Immune Network for Feature Extracting

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6728))

Abstract

focusing on “distinctiveness” and “effectiveness” of algorithms inspired by natural immune system, a novel artificial immune network algorithm named immune feature extracting network (IFEN) is proposed to realize the function of feature data extracting in this paper. Based on comprehensive analysis of mechanism of natural immune system and current researching works of artificial immune system (AIS), a modified paradigm of artificial immune network (AIN) and a new mutation operation are designed to adapt to decrease the size of sample data set and extract feature data from the data set with noise. The proposed algorithm is supposed to be used as a data preprocessing method with functions of data compression and data cleansing. Preliminary experiments show that the quality of the data set processed by IFEN is apparently improved and the size is compressed.

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Author information

Authors and Affiliations

  1. School of Computer Science, South China Normal University, Guangzhou, China

    Hong Ge & XueMing Yan

Authors
  1. Hong Ge
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  2. XueMing Yan
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception, Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, 100871, Beijing, China

    Ying Tan

  2. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, 215123, Suzhou, China

    Yuhui Shi

  3. Automation College, Chongqing University, 400030, Chongqing, China

    Yi Chai

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

    Guoyin Wang

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© 2011 Springer-Verlag Berlin Heidelberg

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Cite this paper

Ge, H., Yan, X. (2011). A Modified Artificial Immune Network for Feature Extracting. In: Tan, Y., Shi, Y., Chai, Y., Wang, G. (eds) Advances in Swarm Intelligence. ICSI 2011. Lecture Notes in Computer Science, vol 6728. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21515-5_48

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  • DOI: https://doi.org/10.1007/978-3-642-21515-5_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21514-8

  • Online ISBN: 978-3-642-21515-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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