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The Application of Ant Colony Algorithm and Artificial Neural Network in Tax Assessment

机译:蚁群算法和人工神经网络在税收评估中的应用

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摘要

Tax assessment is an important and complex task in tax administration. A large number of data is involved in the process. Hence, a scientific model is in demanding. In this paper, we present a model which integrates the ant colony algorithm into artificial neural network to improve the performance of neural network in judgment of whether the taxpayer is credible. In details, we use ant colony algorithm to train the weights of artificial neural network, and this method could avoid some defects of artificial neural network. The simulation result validates the effectiveness of our method.
机译:税收评估是税收管理中一项重要而复杂的任务。该过程涉及大量数据。因此,对科学模型的要求很高。在本文中,我们提出了一个模型,该模型将蚁群算法集成到人工神经网络中以提高神经网络在判断纳税人是否可信方面的性能。在细节上,我们采用蚁群算法来训练人工神经网络的权重,这种方法可以避免人工神经网络的一些缺陷。仿真结果验证了该方法的有效性。

著录项

  • 来源
    《ChinaVR'2010 : Abstract.》|2010年|p.1433-1436|共4页
  • 会议地点 Shanghai(CN)
  • 作者单位

    School of Communication and Information Engineering, Shanghai University, Shanghai, P.R.China;

    School of Communication and Information Engineering, Shanghai University, Shanghai, P.R.China;

    School of Communication and Information Engineering, Shanghai University, Shanghai, P.R.China;

    School of Communication and Information Engineering, Shanghai University, Shanghai, P.R.China;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 计算机仿真;计算机仿真;
  • 关键词

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