期刊导航

论文摘要

基于神经网络和属性距离矩阵的中药方剂功效归约算法

A Chinese Traditional Medicine Prescription Effect Reduction AlgorithmBased on Artificial Neural Network and Property Distance Matrix

作者:彭京(四川大学 计算机学院,四川 成都 610065);唐常杰(四川大学 计算机学院,四川 成都 610065);曾涛(四川大学 计算机学院,四川 成都 610065)

Author:(School of Computer,Sichuan Univ.,Chengdu 610065,China);(School of Computer,Sichuan Univ.,Chengdu 610065,China);(School of Computer,Sichuan Univ.,Chengdu 610065,China)

收稿日期:2005-05-11          年卷(期)页码:2006,38(1):92-97

期刊名称:工程科学与技术

Journal Name:Advanced Engineering Sciences

关键字:神经网络; 高维数据归约; 相似度; 方剂功效; 矢量; 相似距离

Key words:ANN;high dimensions reduction;similarity;prescription effect;vector;similarity distance

基金项目:国家自然科学基金(60473071);四川省重点科技计划项目(04SG1640);高等学校博士学科点专项科研基金SRFDP(20020610007)和国家中医药管理局基金SATCM资助项目(2003JP40)

中文摘要

针对中药方剂功效归纳问题,提出了一种基于人工神经网络新的高维数据归约方法。新方法利用属性间先验的相似信息,得到属性距离矩阵,然后将矩阵引入神经网络,通过训练神经网络得到最终数据归约结果。依据这个方法实现了一个中药方剂分析系统。实验表明,新方法在中药方剂功效的自动归纳中获得很好的效果。

英文摘要

A novel reduction method of high dimensions based on artificial neural network was proposed for the effect reduction of Chinese traditional medicine prescription. Based on the similarity information between properties, it created a property distance matrix.The matrix was loaded into an artificial neural network, and through training the artificial neural network, it got the reduce result of high dimensions. Based on the new method, a prescription analyze system of Chinese traditional medicine was implemented. The efficiency of the new method was proved by experiments in effect reduction of Chinese traditional medicine.

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