Study on Mongolian Medicine Prescription Classification Method Based on Fuzzy C-means Algorithm
10.3969/j.issn.1005-5304.2017.08.022
- VernacularTitle:基于模糊C均值聚类算法的蒙医方剂类别划分方法研究
- Author:
Chunsheng ZHANG
;
Tuya BAO
;
Yan LI
- Keywords:
fuzzy c-means algorithm;
hard c-means algorithm;
Mongolian medicine;
prescription;
clustering;
compatibility
- From:
Chinese Journal of Information on Traditional Chinese Medicine
2017;24(8):99-103
- CountryChina
- Language:Chinese
-
Abstract:
Objective To classify Mongolian medicine prescription by using fuzzy c-means algorithm (FCM) and hard c-means algorithm (HCM); To explore the rationality of two kinds of clustering algorithm. Methods 27 Mongolian medicine prescriptions for treating Heiyi disease from Chuan Tong Meng Yao Yu Fang Ji were set as experimental data, and the data were preprocessed first. MS Visual Studio 2010 platform was used, and C# language was used for research and development. Chinese version and Mogolian version were implemented with WindowFrom and WPF technology, respectively. The medicine prescriptions were classified into 3, 4, 5, and 6 types by using FCM and HCM. Results All categorization with zero classification showed the existence of inclusion phenomena. The medicine in the classification results obtained by the two kinds of clustering algorithm did not exist cross. FCM could produce clustering results with smaller quantity difference and the more uniform classification compared with HCM. Conclusion The two algorithms are correct and reasonable, in which FCM algorithm has better clustering effect, and can be widely used in Mongolian prescription analysis, with a purpose to provide data supports for the research and development of new medicine.
