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Reduction of rough set attribute based on immune clone selection

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Abstract

A novel attribute reduction approach of rough set based on immune clone selection is proposed. In this method, the approximation quality and attribute set were adopted as evolution object and antibody, respectively. On the basis of the inherent distribution within the immune response, the global optimization of the antibody was realized through parallel local optimization. Moreover, the diversity of the antibody population was maintained with the affinity maturation and renewal of the antibody. Thus, the stable multi-optimal solutions can be preserved. In addition, the machinery fault data were analyzed by this method, and the attribute reduction sets were obtained further to satisfy the demand of feature selection in machinery diagnosis.

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Authors and Affiliations

  1. School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, 710049, China

    Liang Lin

  2. The State Key Lab for Manufacturing System Engineering, Xi’an Jiaotong University, Xi’an, 710049, China

    Xu Guang-hua

Authors
  1. Liang Lin
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  2. Xu Guang-hua
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Correspondence to Liang Lin.

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Translated from Journal of Xi’an Jiaotong University, 2005, 39(11) (in Chinese)

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Liang, L., Xu, Gh. Reduction of rough set attribute based on immune clone selection. Front. Mech. Eng. China 1, 413–417 (2006). https://doi.org/10.1007/s11465-006-0049-4

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  • DOI: https://doi.org/10.1007/s11465-006-0049-4

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