A Back Propagation Artificial Neural Network Applied to Body Constitution in Traditional Chinese Medicine Modeling

Zhi Biao Li

doi:10.4028/www.scientific.net/AMR.659.123

Paper Titles

Classification Algorithm Based on Category Attribute’s Mathematical Expectation
p.103

An Iterative Algorithm on the Spectral Radius of a Kind of Centrosymmetric Matrix
p.108

A Simulation and Prediction Method of the Height of Wheat Based on BP Neural Networks and the Ant Colony Algorithm
p.113

Research on Data Assimilation Methods of Multi-Space-Time Meteroligical and Hydrological Data
p.118

A Back Propagation Artificial Neural Network Applied to Body Constitution in Traditional Chinese Medicine Modeling
p.123

Mining Methods Based on Vague Optimization Evaluation
p.128

Fire Detection Technologies Based on Video Image
p.134

Application of Snakes Model in Metal Fracture Images Processing
p.139

An Efficient View-Point Invariant Detector and Descriptor
p.143

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 659A Back Propagation Artificial Neural Network...

A Back Propagation Artificial Neural Network Applied to Body Constitution in Traditional Chinese Medicine Modeling

Abstract:

In this paper, artificial neural network architecture is introduced to predict the Yin-Yang index of body constitution in traditional Chinese medicine (BCTCM). With pre-processing the inputting data by the median, the collected data is more consistent with the exact value of the characteristic parameters of BCTCM. Quasi-Newton algorithm is used to train the network model to accelerate the convergence speed of network training. Experiments show that, the result showed that they had good prediction accuracies for BCTTCM. The mean absolute error for 10 true measured points was 0.034. Therefore, the prediction model of BCTCM Yin-Yang index with BP neural network is doable.

You might also be interested in these eBooks

Advanced Materials and Computer Science II

View Preview

Info:

Periodical:

Advanced Materials Research (Volume 659)

Pages:

123-127

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.659.123

Citation:

Cite this paper

Online since:

January 2013

Authors:

Zhi Biao Li

Keywords:

Artificial Neural Network (ANN), Back Propagation Algorithm (BPA), Constitution, Quasi-Newton Algorithm, Traditional Chinese Medicine

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Q. Wang, Theory of Body constitution in traditional Chinese medicine, People's Medical Publishing House, Beijing, 2005, pp.77-85.

Google Scholar

[2] Y. Wang, Study and Improvement of the Clustering Method Applying in the Constitutional Classification, Xi'an University of Electronic Science and Technology. 2007, pp.25-26.

Google Scholar

[3] L. Q. Han, Artificial neural networks theory, design and application, Chemical industry publishing house, Beijing, 2007, pp.47-61.

Google Scholar

[4] Q. Wang, Research Status and Prospects on Theory of body constitution in traditional Chinese medicine, Journal of Shandong college of traditional Chinese medicine, vol. 18, 2. 1994, pp.74-81.

Google Scholar

[5] Institute of Chinese Medicine, Classification and Standard of Body constitution in traditional Chinese medicine, World journal of integrated traditional and western medicine, vol. 4, 4. 2009, pp.303-304.

Google Scholar

[6] Y. F. Luo, X. G. Liu, K. Y. Song, Y. X. Liu, S. G. Yu, Investigation of Body constitution in traditional Chinese medicine of Yin and Yang from the physical impact of shift work on the human body, Chinese medicine, vol. 13, 5. 1998, pp.6-9.

Google Scholar

[7] Y. Li, L. Zhang, "Research on intrusion detection based on the Quasi-Newton algorithm in neural networks, Information Technology, 11. 2008, pp.74-77.

Google Scholar