基于免疫聚类的RBF神经网络在中医舌诊诊断中的应用  

APPLYING IMMUNE CLUSTERING BASED RBF NEURAL NETWORKS IN TONGUE INSPECTION OF TCM DIAGNOSIS

作　　者：谢铮桂[1,2] 韦玉科[1] 钟少丹[1,2] 

机构地区：[1]广东工业大学计算机学院,广东广州510090 [2]韩山师范学院数学与信息技术系,广东潮州521041

出　　处：《计算机应用与软件》2009年第4期42-43,54,共3页Computer Applications and Software

基　　金：国家自然科学基金项目(30472122)。

摘　　要：研究基于人工免疫聚类的RBF(Radial-Basis Function)神经网络应用于中医舌诊诊断,构建一个中医舌诊智能诊断的神经网络模型,旨在提高模型的诊断能力和收敛速度。对输入样本集进行数据归一化处理,采用改进的基于免疫聚类的RBF算法进行学习、训练。以肝病病证诊断进行仿真,结果表明:该中医舌诊智能诊断系统具有诊断能力强、收敛速度快,泛化能力强等特点。因此,基于人工免疫聚类的RBF神经网络应用于中医舌诊诊断的研究是可行的,有效的。The paper focuses on applying the artificial immune clustering based RBF neural networks in tongue inspection of TCM diagnosis. A neural networks model for intelligent tongue inspection of TCM diagnosis was constructed aiming at improving the model＇s diagnostic ability and convergence rate. The data in input sample set were treated in normalization, and the improved immune clustering based RBF algorithm was used in learning and training. The hepatic disease symptom is used for simulation. The experimental result demonstrated that the intelligent tongue inspection of TCM diagnosis system has good diagnostic ability, fast convergence rate and good generalization ability. So the research on RBF neural networks based on artificial immune clustering in tongue inspection of TCM diagnosis is feasible and effective.

关 键 词：人工神经网络 舌诊 人工免疫聚类 径向基函数神经网络 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TP277[自动化与计算机技术—控制科学与工程]