| 基于BP神经网络的税收预测模型 |
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| 引用本文： | 张绍秋,胡跃明.基于BP神经网络的税收预测模型[J].华南理工大学学报(自然科学版),2006,34(6):55-58. |
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| 作者姓名： | 张绍秋 胡跃明 |
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| 作者单位： | 华南理工大学,自动化科学与工程学院,广东,广州,510640 |
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| 摘 要： | 在分析影响税收主要因素的基础上，将反向传播（BP）神经网络理论应用于税收的预测．首先对初始数据进行预处理，使其适应BP神经网络学习的要求，然后建立基于BP神经网络的税收预测模型．采用实际数据对模型进行验证，并将其与传统的统计模型相比较，证明了基于BP神经网络的税收预测模型有较高的精度和较强的实用性．
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| 关 键 词： | 税收预测 预测模型 神经网络 |
| 文章编号： | 1000-565X（2006）06-0055-04 |
| 收稿时间： | 2005-06-07 |
| 修稿时间： | 2005年6月7日 |
Taxation Forecasting Model Based on BP Neural Network |
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| Zhang Shao-qiu,Hu Yue-ming.Taxation Forecasting Model Based on BP Neural Network[J].Journal of South China University of Technology(Natural Science Edition),2006,34(6):55-58. |
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| Authors: | Zhang Shao-qiu Hu Yue-ming |
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| Institution: | College of Automation Science and Engineering, South China Univ. of Tech. , Guangzhou 510640, Guangdong, China |
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| Abstract: | In this paper,the BP(Back Propagation) neural network theory is applied to forecast taxation after analyzing the major factors affecting the tax.During the investigation,the original data are preprocessed to meet the requirements of the study in BP neural network,and a taxation forecasting model based on BP neural network is established.The proposed model is then verified by using actual data and is compared with the traditional statistic model.It is concluded that the proposed model is of high precision and great applicability. |
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| Keywords: | taxation forecasting forecasting model neural network |
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