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Cat Swarm Optimization applied to alcohol use disorder identification

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Abstract

(Aim) Alcohol use disorder may put health at risk and cause serious health problems. It is of increasing importance to identify alcohol use disorder as early as possible. (Method) This study proposed a computer-vision based technique. The dataset was scanned by magnetic resonance imaging in China participating hospitals. Afterwards, we combined wavelet entropy, two-layer feedforward neural network, and cat swarm optimization (CSO). The CSO mimics the behavior of cat and is composed of two modes: seeking mode and tracing mode. (Results) The results showed that our method achieves a sensitivity of 91.84 ± 1.66%, a specificity of 92.40 ± 1.22%, and an accuracy of 92.13 ± 0.70%. Using grid searching approach, we found the classification performance is the best, when decomposition level is assigned with 2 and the mixture ratio is assigned with a value of 0.8. (Conclusion) The CSO is superior to four bioinspired algorithms: genetic algorithm, immune genetic algorithm, particle swarm optimization, and chaotic self-adaptive particle swarm optimization. In addition, our proposed alcoholism identification system is superior to four state-of-the-art alcoholism detection approaches.

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Acknowledgments

This paper is financially supported by Natural Science Foundation of China (61602250), Natural Science Foundation of Jiangsu Province (BK20150983), Project of Science and Technology of Henan Province (172102210272), Program for Science & Technology Innovation Talents of Henan Province (174100510009), Open fund for Jiangsu Key Laboratory of Advanced Manufacturing Technology (HGAMTL1601, HGAMTL-1703), Open fund of Key Laboratory of Guangxi High Schools Complex System and Computational Intelligence (2016CSCI01), Open Fund of Guangxi Key Laboratory of Manufacturing System & Advanced Manufacturing Technology (17-259-05-011 K)., Henan Key Research and Development Project (182102310629), National key research and development plan (2017YFB1103202)

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Authors and Affiliations

  1. School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, Henan, 454000, People’s Republic of China

    Yu-Dong Zhang & Junding Sun

  2. Department of Informatics, University of Leicester, Leicester, LE1 7RH, UK

    Yu-Dong Zhang

  3. Department of Psychiatry, Nanjing Medical University, Nanjing, 210029, Jiangsu, China

    Yuxiu Sui

  4. National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410083, People’s Republic of China

    Guihu Zhao

  5. School of Digital Media, Jiangnan University, Wuxi, 214122, China

    Pengjiang Qian

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  1. Yu-Dong Zhang
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  2. Yuxiu Sui
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  3. Junding Sun
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  4. Guihu Zhao
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Correspondence to Yu-Dong Zhang, Yuxiu Sui, Junding Sun, Guihu Zhao or Pengjiang Qian.

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Zhang, YD., Sui, Y., Sun, J. et al. Cat Swarm Optimization applied to alcohol use disorder identification. Multimed Tools Appl 77, 22875–22896 (2018). https://doi.org/10.1007/s11042-018-6003-8

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  • DOI: https://doi.org/10.1007/s11042-018-6003-8

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