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Feasibility, Advantages and Disadvantages of BP Neural Network Applied in TCM Constitution Identifications

Received: 15 November 2019     Accepted: 19 February 2020     Published: 23 March 2020
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Abstract

Objective This study will analyze the feasibility, advantages and disadvantages of the application of BP neural network in TCM physique identification based on the characteristics of TCM physique identification, so as to obtain a more accurate physique typing, which makes the use of TCM for identifying diseases more widely and convenient. science. Methods The feedforward BP neural network model was used to operate the data to construct a BP neural network model suitable for TCM physique identification. We will carry out a questionnaire survey on community people aged 40 to 70 years old in Longjiang Town, Shunde District, Foshan City, Guangdong Province, collect data models through the TCM physique identification form and make predictions on the population's physique; then match the questionnaire content with the final results Among them, 525 sets of data are used as the training set input model, and the remaining 132 sets of data are used as the test set. After error testing and comparison analysis with the classic prediction model. The results show that the BP neural network method can predict the TCM constitution type of the community based on the questionnaire results of the TCM Constitution Identification Form. Conclusion The application of BP neural network in the classification of TCM constitutions has high reliability, simple operation, low cost, and convenient methods suitable for community promotion.

Published in Asia-Pacific Journal of Computer Science and Technology (Volume 1, Issue 4)
Page(s) 34-38
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2020. Published by Science Publishing Group

Keywords

BP Neural Network, TCM Constitution Identification, Feasibility

References
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Cite This Article
  • APA Style

    Xie Fangrong, Zhou Xiaoyun, Han Liang, Shi Zhongfeng, Chen Guanhao, et al. (2020). Feasibility, Advantages and Disadvantages of BP Neural Network Applied in TCM Constitution Identifications. Asia-Pacific Journal of Computer Science and Technology, 1(4), 34-38.

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    ACS Style

    Xie Fangrong; Zhou Xiaoyun; Han Liang; Shi Zhongfeng; Chen Guanhao, et al. Feasibility, Advantages and Disadvantages of BP Neural Network Applied in TCM Constitution Identifications. Asia-Pac. J. Comput. Sci. Technol. 2020, 1(4), 34-38.

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    AMA Style

    Xie Fangrong, Zhou Xiaoyun, Han Liang, Shi Zhongfeng, Chen Guanhao, et al. Feasibility, Advantages and Disadvantages of BP Neural Network Applied in TCM Constitution Identifications. Asia-Pac J Comput Sci Technol. 2020;1(4):34-38.

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  • @article{10044881,
      author = {Xie Fangrong and Zhou Xiaoyun and Han Liang and Shi Zhongfeng and Chen Guanhao and Huang Haiquan and Cheng Qi and Chen Ziqiang and Hu Jinyuan and Song Yuhong and Xu Shu},
      title = {Feasibility, Advantages and Disadvantages of BP Neural Network Applied in TCM Constitution Identifications},
      journal = {Asia-Pacific Journal of Computer Science and Technology},
      volume = {1},
      number = {4},
      pages = {34-38},
      url = {https://www.sciencepublishinggroup.com/article/10044881},
      abstract = {Objective This study will analyze the feasibility, advantages and disadvantages of the application of BP neural network in TCM physique identification based on the characteristics of TCM physique identification, so as to obtain a more accurate physique typing, which makes the use of TCM for identifying diseases more widely and convenient. science. Methods The feedforward BP neural network model was used to operate the data to construct a BP neural network model suitable for TCM physique identification. We will carry out a questionnaire survey on community people aged 40 to 70 years old in Longjiang Town, Shunde District, Foshan City, Guangdong Province, collect data models through the TCM physique identification form and make predictions on the population's physique; then match the questionnaire content with the final results Among them, 525 sets of data are used as the training set input model, and the remaining 132 sets of data are used as the test set. After error testing and comparison analysis with the classic prediction model. The results show that the BP neural network method can predict the TCM constitution type of the community based on the questionnaire results of the TCM Constitution Identification Form. Conclusion The application of BP neural network in the classification of TCM constitutions has high reliability, simple operation, low cost, and convenient methods suitable for community promotion.},
     year = {2020}
    }
    

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  • TY  - JOUR
    T1  - Feasibility, Advantages and Disadvantages of BP Neural Network Applied in TCM Constitution Identifications
    AU  - Xie Fangrong
    AU  - Zhou Xiaoyun
    AU  - Han Liang
    AU  - Shi Zhongfeng
    AU  - Chen Guanhao
    AU  - Huang Haiquan
    AU  - Cheng Qi
    AU  - Chen Ziqiang
    AU  - Hu Jinyuan
    AU  - Song Yuhong
    AU  - Xu Shu
    Y1  - 2020/03/23
    PY  - 2020
    T2  - Asia-Pacific Journal of Computer Science and Technology
    JF  - Asia-Pacific Journal of Computer Science and Technology
    JO  - Asia-Pacific Journal of Computer Science and Technology
    SP  - 34
    EP  - 38
    PB  - Science Publishing Group
    UR  - http://www.sciencepg.com/article/10044881
    AB  - Objective This study will analyze the feasibility, advantages and disadvantages of the application of BP neural network in TCM physique identification based on the characteristics of TCM physique identification, so as to obtain a more accurate physique typing, which makes the use of TCM for identifying diseases more widely and convenient. science. Methods The feedforward BP neural network model was used to operate the data to construct a BP neural network model suitable for TCM physique identification. We will carry out a questionnaire survey on community people aged 40 to 70 years old in Longjiang Town, Shunde District, Foshan City, Guangdong Province, collect data models through the TCM physique identification form and make predictions on the population's physique; then match the questionnaire content with the final results Among them, 525 sets of data are used as the training set input model, and the remaining 132 sets of data are used as the test set. After error testing and comparison analysis with the classic prediction model. The results show that the BP neural network method can predict the TCM constitution type of the community based on the questionnaire results of the TCM Constitution Identification Form. Conclusion The application of BP neural network in the classification of TCM constitutions has high reliability, simple operation, low cost, and convenient methods suitable for community promotion.
    VL  - 1
    IS  - 4
    ER  - 

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Author Information
  • First People's Hospital Affiliated to Guangzhou Medical University, Guangzhou, China

  • First People's Hospital Affiliated to Guangzhou Medical University, Guangzhou, China

  • Health Departments, Guangdong Pharmaceutical University, Guangzhou, China

  • Health Departments, Guangdong Pharmaceutical University, Guangzhou, China

  • Health Departments, Guangdong Pharmaceutical University, Guangzhou, China

  • Guangdong Yisheng Information Technology Co., Ltd., Guangzhou, China

  • Guangdong Yisheng Information Technology Co., Ltd., Guangzhou, China

  • Guangdong Yisheng Information Technology Co., Ltd., Guangzhou, China

  • Guangdong Shengshijianwang Health Management Co., Ltd., Guangzhou, China

  • First People's Hospital Affiliated to Guangzhou Medical University, Guangzhou, China

  • Chinese Academy of Sciences University Shenzhen Hospital (Guangming), Shenzhen, China

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