自适应神经模糊推理系统用于症候诊断的研究  

Application of Adaptive Network-based Fuzzy Inference System in Syndrome Diagnosis

作　　者：李建生[1] 胡金亮[1] 岳彩青[2] 

机构地区：[1]河南中医学院老年医学研究所,河南郑州450003 [2]信息工程大学理学院信息科技研究所,河南郑州450001

出　　处：《计算机仿真》2006年第3期117-119,共3页Computer Simulation

摘　　要：提出了基于T-S模型(Takagi-Sugeno型)的自适应神经网络模糊推理系统(AdaptiveNetwork-basedFuzzyInferenceSystem,ANFIS),介绍了高木—关野(Takagi-Sugeno型)模型结构和自适应神经网络模糊推理系统的结构和算法。该文采用减法聚类初始化模糊推理系统模型,把神经网络学习机制引入到逻辑推理中,使传统的逻辑推理不仅具有逻辑思维及语言表达能力而且具有自学习和联想能力,通过2型糖尿病症候数据库验证了ANFIS用于症候诊断的合理性和有效性。提示自适应神经网络模糊推理系统适合中医症候诊断的研究。An Adaptive Network - based Fuzzy Inference System based on T - S model is presented in this paper. At first, this paper introduces the structure of T - S model and the structure and algorithm of Adaptive Network - based Fuzzy Inference System. The model of ANFIS is initialized by subclust in this paper. Since neural network is applied to Fuzzy Inference System, the conventional fuzzy inference system has not only the ability of logic reason and language expression but also the ability of self- learning and self- imaging. The result tested by the document Data Base of type - 2 diabetes mellites verifies the validity and reasonableness of applying ANFIS to syndrome diagosis. So It is practical for ANFIS to be applied to the study of TCM syndrome diagnosis.

关 键 词：高木-关野模型 自适应神经模糊系统 减法聚类 症候诊断 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]