Feasibility, Advantages and Disadvantages of BP Neural Network Applied in TCM Constitution Identifications
Asia-Pacific Journal of Computer Science and Technology
Volume 1, Issue 4, December 2019, Pages: 34-38
Received: Nov. 15, 2019; Accepted: Feb. 19, 2020; Published: Mar. 23, 2020
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Authors
Xie Fangzhen, First People's Hospital Affiliated to Guangzhou Medical University, Guangzhou, China
Zhou Xiaoyu, 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 Guanha, 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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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.
Keywords
BP Neural Network, TCM Constitution Identification, Feasibility
To cite this article
Xie Fangzhen, Zhou Xiaoyu, Han Liang, Shi Zhongfeng, Chen Guanha, Huang Haiquan, Cheng Qi, Chen Ziqiang, Hu Jinyuan, Song Yuhong, Xu Shu, Feasibility, Advantages and Disadvantages of BP Neural Network Applied in TCM Constitution Identifications, Asia-Pacific Journal of Computer Science and Technology. Vol. 1, No. 4, 2019, pp. 34-38. doi: 10044881
Copyright
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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