Please wait a minute...
New Technology of Library and Information Service  2011, Vol. 27 Issue (12): 69-73    DOI: 10.11925/infotech.1003-3513.2011.12.11
Current Issue | Archive | Adv Search |
Research on Data Mining of Complex Multi-dimensional Fingerprint Data of TCM
Tong Yifu, Huang Chunyi
School of Public Administration, Sichuan University, Chengdu 610064, China
Download: PDF(569 KB)   HTML  
Export: BibTeX | EndNote (RIS)      
Abstract  Grounded on the R open source statistic environment, this paper builds a data mining model on the complex HPLC multi-dimensional fingerprint data with visualization analysis. The result fully reflects that PCA can be used as a model to reveal the principles of multi-dimensional data, and verifies the validity and practicality of principal component and cluster analysis and neural network to reveal the character of multi-dimensional data. Finally, based on the results of PCA and cluster analysis, this paper builds a training network model through techniques of machine learning and other related statistical algorithm to predict the habitat of unknown TCM sample, which supplies sufficient evidences to the TCM quality control.
Key wordsMulti-dimensional information      Data mining      Principal component and cluster analysis      Neural network     
Received: 25 October 2011      Published: 02 February 2012



Cite this article:

Tong Yifu, Huang Chunyi. Research on Data Mining of Complex Multi-dimensional Fingerprint Data of TCM. New Technology of Library and Information Service, 2011, 27(12): 69-73.

URL:     OR

[1] 宋炳生,王曙东,李克. 中药指纹图谱及其对中药发展的影响[J].中草药,2002,33(11):961-963.

[2] 罗国安,王义明,曹进. 多维多息特征谱及其应用[J].中草药,2000,31(6):395-397.

[3] 张晓帆,董鸿晔,金杰,等. 基于SQL Server 2005的数据挖掘技术在中药指纹图谱数据分析中的应用[J].沈阳药科大学学报,2010,27(3):205-212.

[4] 郝燕,姜楠,孙国祥,等. 基于主成分分析的中药色谱指纹图谱多维多息特征数据挖掘方法研究[J].中南药学,2007,5(3):267-272.

[5] 薛毅,陈立萍. R统计建模与R软件[M].北京:清华大学出版社,2007.

[6] 张东方,沙明,杨松松,等.人工神经网络在中药领域中的应用现状及前景[J]. 中草药, 2003,34(1):89-91.

[7] 韩力群. 人工神经网络理论、设计及应用[M]. 北京:化学工业出版社, 2002.
[1] Yong Zhang,Shuqing Li,Yongshang Cheng. Mining Algorithm for Weighted Association Rules Based on Frequency Effective Length[J]. 数据分析与知识发现, 2019, 3(7): 85-93.
[2] Zhenyu He,Xiangxiang Dong,Qinghua Zhu. Classifying Baidu Encyclopedia Entries with User Behaviors[J]. 数据分析与知识发现, 2019, 3(6): 117-122.
[3] Kan Liu,Lu Chen. Deep Neural Network Learning for Medical Triage[J]. 数据分析与知识发现, 2019, 3(6): 99-108.
[4] Wancheng Chen,Haoran Dai,Yinghan Jin. Appraising Home Prices with HEDONIC Model: Case Study of Seattle, U.S.[J]. 数据分析与知识发现, 2019, 3(5): 19-26.
[5] Quan Lu,Anqi Zhu,Jiyue Zhang,Jing Chen. Research on User Information Requirement in Chinese Network Health Community: Taking Tumor-forum Data of Qiuyi as an Example[J]. 数据分析与知识发现, 2019, 3(4): 22-32.
[6] Dongmei Mu,Hui Fa,Ping Wang,Jing Sun. Research on Disease Risk Factors on Structural Equation Model[J]. 数据分析与知识发现, 2019, 3(4): 80-89.
[7] Yuemei Xu,Sining Lv,Lianqiao Cai,Xiaoya Zhang. Analyzing News Topic Evolution with Convolutional Neural Networks and Topic2Vec[J]. 数据分析与知识发现, 2018, 2(9): 31-41.
[8] Xiaoyu Ma,Han Zhang,Yuhong Zhao. Building Childhood Asthma Prediction Model with Artificial Neural Network and BRFSS Database[J]. 数据分析与知识发现, 2018, 2(8): 10-15.
[9] Hu Meng,Xiaobei Liang,Yixiong Yang,Min Li. Evaluating and Optimizing Supply Chains with LMBP Algorithm[J]. 数据分析与知识发现, 2018, 2(11): 37-45.
[10] Yuying Wu,Ping Sun,Xijun He,Guorui Jiang. Predicting Transactions Among Agents in Patent Transfer Weighted Networks for New Energy[J]. 数据分析与知识发现, 2018, 2(11): 73-79.
[11] Yanhui Xiao,Xin Wang,Wen’gang Feng,Huawei Tian,Shaozhong Wu,Lihua Li. Predicting Crime Locations Based on Long Short Term Memory and Convolutional Neural Networks[J]. 数据分析与知识发现, 2018, 2(10): 15-20.
[12] Xiaoxi Huang,Hanyu Li,Rongbo Wang,Xiaohua Wang,Zhiqun Chen. Recognizing Metaphor with Convolution Neural Network and SVM[J]. 数据分析与知识发现, 2018, 2(10): 77-83.
[13] Yongnan Li. Using Bayes Theory to Classify Counter Terrorism Intelligence[J]. 数据分析与知识发现, 2018, 2(10): 9-14.
[14] Jiaheng Hu,Yonghua Cen,Chengyao Wu. Constructing Sentiment Dictionary with Deep Learning: Case Study of Financial Data[J]. 数据分析与知识发现, 2018, 2(10): 95-102.
[15] Dongmei Mu,Ping Wang,Danning Zhao. Reducing Data Dimension of Electronic Medical Records: An Empirical Study[J]. 数据分析与知识发现, 2018, 2(1): 88-98.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938