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投稿时间：2006-12-28
投稿时间：2006-12-28
中文摘要: 了解决中药方剂的功效约简问题，将模糊神经元和径向基函数引入神经网络，提出了基于模糊神经网络的方剂功效约简算法PERA(Prescription Effect Reduction Algorithm)，设计了方剂功效约简模糊神经网络EFNN(Effect Fuzzy Neural Network)。通过大量实验表明，与传统的基于神经网络和粗糙集的属性约简算法相比，PERA算法功效约简的准确率较高，一般在90％以上，功效约简的完整率优势明显，平均高出约40%，系统运行时间明显小于传统神经网络。
Abstract:To solve the problem of reducing prescription effects of traditional Chinese medicine,the fuzzy neuron and the radial basis function was applied to the neural network, a prescription effect reduction algorithm named PERA (Prescription Effect Reduction Algorithm) based on fuzzy neural network was proposed, and a prescription effect reduction system named EFNN (Effect Fuzzy Neural Network) was developed. Experiments demonstrated that the proposed method is better than other traditional attribute reduction algorithms, such as artificial neural network and rough set. The precision of effect reduction of PERA is greater than 90%, the recall is about 40%, greater than traditional attribute reduction algorithms, and its running time is less than traditional neural networks obviously.
文章编号：20080221 中图分类号： 文献标志码：
基金项目:国家自然科学基金资助项目(60473071)；国家中医药管理局基金SATCM资助项目(2003JP40)；中国博士后科学基金资助项目(20060400002)；四川省青年软件创新工程资助项目(2005AA0816)
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引用文本：
乔少杰,唐常杰,韩楠.基于模糊神经网络的方剂功效约简算法[J].工程科学与技术,2008,40(2):107-111.
.Prescription Effect Reduction Algorithm Based on Fuzzy Neural Network[J].Advanced Engineering Sciences,2008,40(2):107-111.
引用文本：
乔少杰,唐常杰,韩楠.基于模糊神经网络的方剂功效约简算法[J].工程科学与技术,2008,40(2):107-111.
.Prescription Effect Reduction Algorithm Based on Fuzzy Neural Network[J].Advanced Engineering Sciences,2008,40(2):107-111.