提出一种基于自生成神经网络(SGNN)的税收申报欺诈检测方法。
An approach of fraud detection in tax declaration based on self-generating neural networks (SGNN) is proposed.
自生成神经网络（SGNN）是一类自组织神经网络，它不需要用户指定网络结构和学习参数，而且不需要迭代学习，是一类特点突出的神经网络。
Self-generating neural network (SGNN) is a self-organization neural network, whose network structures and parameters need not to be set by users, and its learning process needs no iteration.
对此，本文改进了R BF神经网络的学习算法，提出了一种基于聚类的动态自生成隐含层节点的思想。
As for it, by improving learning algorithm of traditional RBF neural network, a new dynamic cluster-based self-generated method for hidden layer nodes is proposed.
对此，本文改进了R BF神经网络的学习算法，提出了一种基于聚类的动态自生成隐含层节点的思想。
As for it, by improving learning algorithm of traditional RBF neural network, a new dynamic cluster-based self-generated method for hidden layer nodes is proposed.
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