从模糊神经网络技术探讨普通感冒的证候特征  

Syndrome Characteristics of Fuzzy Neural Network Technology on the Common Cold

作　　者：王至婉[1,2] 胡金亮[2] 李建生[1] 张甜[1] 

机构地区：[1]河南中医学院,河南郑州450046 [2]河南中医学院第一附属医院,河南郑州450001

出　　处：《中医学报》2013年第3期334-336,共3页Acta Chinese Medicine

基　　金：河南省高校新世纪优秀人才支持计划(编号:2006HANCET-05)

摘　　要：目的:运用模糊神经网络技术探讨普通感冒常见证候及其主症、次症的特征。方法:收集7所三级甲等医院普通感冒患者资料,应用Epidata软件建立数据库;运用MATLAB 6.5软件进行编程。从互联网搜集了Fisher-iris数据,选取人工神经网络与模糊系统方法,采用动态kehonen网络,获得最优模糊规则。结果:最终获取20个模糊规则,通过规则转换及设定筛选出5个常见证候,即风寒证、风热证、风燥证、痰热证及痰湿证,并对其主症、次症特征进行筛选。结论:普通感冒常见证候有5种,其主症、次症特征可作为临床辨证的参考;模糊神经网络技术可用于中医证候特征的研究。Objective：To use the common cold syndromes and with secondary characteristics of fuzzy neural network technology. Methods ： To collect 7 hospital patients with common cold data, use Epidata software to establish the database by using MATLABr. 5 software programming. From internet fisher-iris collected data selection, artificial neural network and fuzzy system method, using dynamic kehonen network, obtaining the optimal fuzzy rules. Results： The final 20 to obtain fuzzy rules, through the conversion rules and setting the selected 5 common syndromes, i. e, wind-cold syndrome, wind-heat syndrome,wind dryness, phlegm and dampness, phlegm heat syndrome. And its characteristics were screened with secondary. Conclusion： The common cold syndromes are 5, the primary and secondary disease characteristics can be used as a clinical syndrome differentiation and reference ;fuzzy neural network technology can be used for TCM syndrome characteristics.

关 键 词：普通感冒 证候 模糊神经网络技术 

分 类 号：R2-03[医药卫生—中医学]