关键词: 模糊神经网络, 自组织, 预测模型, 椭球基函数（EBF）

Abstract: Aimed at the problem that the low recognition rate and the poor generalization ability in traditional neural networks, an improved learning algorithm of Self-Organizing Fuzzy Neural Network（SOFNN） is presented. In this algorithm, it is as a basis for modifying, deleting and adding neurons that each neuron output and the sum of all these neurons output in the Ellipsoidal Basis Function（EBF） layer are stored. Then it can obtain effective neurons of the network and reduce the training time of samples. In order to ensure the network convergence, it uses the least square method（RLSE） to estimate the parameters and uses gradient descent method to modify the parameters. Compared with other fuzzy neural networks, the superiority in the accuracy, structure complexity and anti-jamming is effectively verified in the real data set.

Key words: fuzzy neural network, self-organizing, prediction model, Ellipsoidal Basis Function（EBF）