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

Xie Fangrong; Zhou Xiaoyun; Han Liang; Shi Zhongfeng; Chen Guanhao; Huang Haiquan; Cheng Qi; Chen Ziqiang; Hu Jinyuan; Song Yuhong; Xu Shu

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

Xie Fangrong, Zhou Xiaoyun, Han Liang, Shi Zhongfeng, Chen Guanhao, Huang Haiquan, Cheng Qi, Chen Ziqiang, Hu Jinyuan, Song Yuhong, Xu Shu

Published in Asia-Pacific Journal of Computer Science and Technology (Volume 1, Issue 4)

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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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

Xie Fangrong

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

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

Health Departments, Guangdong Pharmaceutical University, Guangzhou, China
Shi Zhongfeng

Health Departments, Guangdong Pharmaceutical University, Guangzhou, China
Chen Guanhao

Health Departments, Guangdong Pharmaceutical University, Guangzhou, China
Huang Haiquan

Guangdong Yisheng Information Technology Co., Ltd., Guangzhou, China
Cheng Qi

Guangdong Yisheng Information Technology Co., Ltd., Guangzhou, China
Chen Ziqiang

Guangdong Yisheng Information Technology Co., Ltd., Guangzhou, China
Hu Jinyuan

Guangdong Shengshijianwang Health Management Co., Ltd., Guangzhou, China
Song Yuhong

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

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

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Plain Text BibTeX RIS

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.

Copy | Download

@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}
}

Copy | Download

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  -

Copy | Download