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《Journal of Sichuan University(Engineering Science Edition)》 2008-02
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Prescription Effect Reduction Algorithm Based on Fuzzy Neural Network

QIAO Shao-jie1,TANG Chang-jie1,HAN Nan2,PENG Jing3,LI Chuan1,QIU Jiang-tao1,JIANG Yong-guang2(1.School of Computer Sci.,Sichuan Univ.,Chengdu 610065,China;2.School of Chinese Basic Medicine,Chengdu Univ.of T.C.M,Chengdu 610075,China;3.School of Electronics Eng.and Computer Sci.,Peking Univ.,Beijing 100871,China)  
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.
【Fund】: 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)
【CateGory Index】: R289;R319
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【Citations】
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