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A fuzzy logic resource allocation and memory cell pruning based artificial immune recognition system

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Abstract

In order to improve the resource allocation mechanism of artificial immune recognition system (AIRS) and decrease the memory cells, a fuzzy logic resource allocation and memory cell pruning based AIRS (FPAIRS) is proposed. In FPAIRS, the fuzzy logic is determined by a parameter, thus, the optimal fuzzy logics for different problems can be located through changing the parameter value. At the same time, the memory cells of low fitness scores are pruned to improve the classifier. This classifier was compared with other classifiers on six UCI datasets classification performance. The results show that the accuracies reached by FPAIRS are higher than or comparable to the accuracies of other classifiers, and the memory cells decrease when compared with the memory cells of AIRS. The results show that the algorithm is a high-performance classifier.

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Authors and Affiliations

  1. School of Information Science and Engineering, Central South University, Changsha, 410083, China

    Ze-lin Deng  (邓泽林) & Guan-zheng Tan  (谭冠政)

  2. School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, 410076, China

    Ze-lin Deng  (邓泽林), Pei He  (何锫) & Ji-xiang Ye  (叶吉祥)

Authors
  1. Ze-lin Deng  (邓泽林)
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  2. Guan-zheng Tan  (谭冠政)
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  3. Pei He  (何锫)
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  4. Ji-xiang Ye  (叶吉祥)
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Corresponding author

Correspondence to Guan-zheng Tan  (谭冠政).

Additional information

Foundation item: Project(61170199) supported by the National Natural Science Foundation of China; Project(11A004) support by the Scientific Research Fund of Education Department of Hunan Province, China

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Deng, Zl., Tan, Gz., He, P. et al. A fuzzy logic resource allocation and memory cell pruning based artificial immune recognition system. J. Cent. South Univ. 21, 610–617 (2014). https://doi.org/10.1007/s11771-014-1980-x

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  • DOI: https://doi.org/10.1007/s11771-014-1980-x

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