Material properties and tensile strength prediction model of traditional Chinese medicine tablets based on PCA-RBF neural network.
10.19540/j.cnki.cjcmm.20190916.303
- Author:
Hai-Ning ZHAO
1
;
Ya-Jing WANG
1
;
Li-Na SHANG
1
;
Meng-Nan ZHOU
1
;
Yi ZHANG
1
;
Xiang-Yin YE
1
;
Yan-Wen WANG
1
;
Di GAO
1
Author Information
1. Tianjin University of Traditional Chinese Medicine Tianjin 301617,China Engineering Research Center of Modern Chinese Medicine Discovery and Preparation Technique,Ministry of Education,Tianjin University of Traditional Chinese Medicine Tianjin 301617,China.
- Publication Type:Journal Article
- Keywords:
powder properties;
prediction model;
principal component analysis;
radial basis neural network;
tablet formability;
tensile strength;
traditional Chinese medicine extract
- MeSH:
Medicine, Chinese Traditional;
Neural Networks, Computer;
Powders;
Tablets;
Technology, Pharmaceutical;
Tensile Strength
- From:
China Journal of Chinese Materia Medica
2019;44(24):5390-5397
- CountryChina
- Language:Chinese
-
Abstract:
This paper constructs a prediction model of material attribute-tensile strength based on principal component analysis-radial basis neural network( PCA-RBF),in order to predict the formability of traditional Chinese medicine tablets. Firstly,design Expert8. 0 software was used to design the dosage of different types of extracts,the mixture of traditional Chinese medicine with different physical properties was obtained,the powder properties of each extract and the tensile strength of tablets were determined,the correlation of the original input layer data was eliminated by PCA,the new variables unrelated to each other were trained as the input data of RBF neural network,and the tensile strength of the tablets was predicted. The experimental results showed that the PCA-RBF model had a good predictive effect on the tensile strength of the tablet,the minimum relative error was 0. 25%,the maximum relative error was2. 21%,and the average error was 1. 35%,which had a high fitting degree and better network prediction accuracy. This study initially constructed a prediction model of material properties-tensile strength of Chinese herbal tablets based on PCA-RBF,which provided a reference for the establishment of effective quality control methods for traditional Chinese medicine preparations.
