数据挖掘技术在地方政府债务风险研究中的应用

发布时间：2018-04-16 21:05

  本文选题：地方政府 + 债务风险　； 参考：《现代电子技术》2017年11期

【摘要】：为了科学、合理地对地方政府债务风险进行评价,提出基于数据挖掘技术的地方政府债务风险评价模型。首先建立地方政府债务风险评价的指标体系,采用灰色关联分析方法确定地方政府债务风险指标的关联系数;然后利用数据挖掘技术——神经网络自动处理数据的优点,建立地方政府债务风险评价模型;最后通过实证分析验证模型的可信度。实证结果表明,与参比地方政府债务风险评估模型相比,该模型提高了地方政府债务风险评价的准确性,加快了地方政府债务风险评价的速度,可以有效降低地方政府债务风险,具有一定的推荐价值。
[Abstract]:In order to evaluate the local government debt risk scientifically and reasonably, a local government debt risk assessment model based on data mining technology is proposed.Firstly, the index system of local government debt risk assessment is established, and the correlation coefficient of local government debt risk index is determined by grey relational analysis, and then the advantage of data mining technology-neural network is used to automatically process the data.The risk assessment model of local government debt is established, and the credibility of the model is verified by empirical analysis.The empirical results show that compared with the reference local government debt risk assessment model, the model improves the accuracy of local government debt risk assessment and accelerates the speed of local government debt risk assessment.Can reduce the local government debt risk effectively, has certain recommendation value.
【作者单位】： 葫芦岛市委党校;
【分类号】：F812.5;TP311.13
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本文编号：1760553