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.

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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.

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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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