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.
