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An Intelligent Algorithm Based on Bacteria Foraging Optimization and Robust Fuzzy Algorithm to Analyze Asthma Data

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Abstract

Asthma has become the serious chronic and the most common disease of hospitalization in children. Recently, the number of children with asthma has increased year by year. Thereafter, the medical community pays much attention to the treatment of asthma. Because of noises or outlier, the resulting factors for asthma are complex. Traditional algorithms usually assume that asthma data are evenly distributed among various classes and might ignore minority classes. Therefore, an intelligent algorithm based on bacterial foraging optimization (BFO) and robust fuzzy algorithm (RFA) is applied to analyze asthma data in this paper. In the proposed algorithm, RFA with the property of robust can reduce the influence of noises or outlier. It can establish the fuzzy model and effectively analyze asthma data. For foraging theory, natural selection trends to eliminate animals with poor foraging strategies and to favor the propagation of genes for animals which have successful foraging strategies. BFO can model the mechanism of natural selection and find the best solution. Consequently, it can enhance the classification accuracy of asthma data. In this paper, asthma data were collected from Mackay Memorial Hospital in Taiwan to test the performance of the proposed algorithm. The performance of the proposed algorithm is supported by simulation results. From simulation results, the classification accuracy of the proposed algorithm outperforms other existing approaches and can help physicians to determine asthma.

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Acknowledgement

The authors would like to thank the Ministry of Science and Technology of the Republic of China, Taiwan, for financially supporting this research under Contract Nos. MOST 105-2632-M-211-001 and MOST 104-2221-E-211-008.

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Authors and Affiliations

  1. Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei City, Taiwan

    Ming-Ren Yang

  2. Department of Information Management, Huafan University, New Taipei City, Taiwan

    Zne-Jung Lee

  3. Department of Information Management, Lan Yang Institute of Technology, Yilan, Taiwan

    Chou-Yuan Lee

  4. Department of Information Management, University of Kang Ning, Tainan City, Taiwan

    Bin-Yu Peng

  5. Department of Mechatronic Engineering, Huafan University, Taipei City, Taiwan

    Bin-Yu Peng & Hsiang Huang

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  1. Ming-Ren Yang
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  2. Zne-Jung Lee
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Correspondence to Zne-Jung Lee.

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Yang, MR., Lee, ZJ., Lee, CY. et al. An Intelligent Algorithm Based on Bacteria Foraging Optimization and Robust Fuzzy Algorithm to Analyze Asthma Data. Int. J. Fuzzy Syst. 19, 1181–1189 (2017). https://doi.org/10.1007/s40815-017-0294-1

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  • DOI: https://doi.org/10.1007/s40815-017-0294-1

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