[1]邓敏,韩玉启.基于支持向量机的大学财务困境预警模型[J].南京理工大学学报(自然科学版),2012,36(03):551-556.
 DENG Min,HAN Yu-qi.Financial Crisis Early Warning Model for Universities Based on Support Vector Machine[J].Journal of Nanjing University of Science and Technology,2012,36(03):551-556.
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基于支持向量机的大学财务困境预警模型
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
36卷
期数:
2012年03期
页码:
551-556
栏目:
出版日期:
2012-06-30

文章信息/Info

Title:
Financial Crisis Early Warning Model for Universities Based on Support Vector Machine
作者:
邓敏; 韩玉启;
南京理工大学经济管理学院;
Author(s):
DENG MinHAN Yu-qi
School of Economics and Management,NUST,Nanjing 210094,China
关键词:
大学 财务困境 预警 支持向量机 误差反向传播神经网络
Keywords:
universities financial crisis early warning support vector machines error back propagation neural network
分类号:
F224;G647.5
摘要:
为了解决大学的财务风险预警模型由于样本稀疏造成预测准确率偏低的问题,该文提出了一种基于支持向量机(SVM)的预警模型的构造方法。选取教育部64所大学的7个财务评价指标并将其分为轻警、重警和巨警3种类别进行了训练计算。与误差反向传播(BP)神经网络模型相比较,在小样本数据条件下,基于SVM的大学财务困境预警模型是大学财务困境预警的有效方法。研究结果可以较好地对大学财务困境进行预警监测。
Abstract:
In order to solve the problem of low prediction accuracy of the financial risk early warning(FREW)model for universities due to sample sparse,this paper presents a method based on support vector machine to construct a FREW model.Seven financial indexes from the 64 universities of China are selected.These index values divided into 3 categories—low,middle and heigh alarming are trained and tested.Compared with the error back propagation neural network model,the FREW model based on support vector machine is a more efficient way in the small sample data conditions.The results can provide an early warming monitor for the financial distress of universities.

参考文献/References:

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Deng Min,Han Yuqi. Pre-warning model of financial distress based on calculus derivation and pattern recognition [J]. Journal of Nanjing University of Science and Technology, 2009, 33( 6) : 834.
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相似文献/References:

[1]邓敏,韩玉启.基于数据推理和模式识别的财务困境预警模型[J].南京理工大学学报(自然科学版),2009,(06):833.
 DENG Min,HAN Yu-qi.Pre-warning Model of Financial Distress Based on Calculus Derivation and Pattern Recognition[J].Journal of Nanjing University of Science and Technology,2009,(03):833.

备注/Memo

备注/Memo:
江苏省教育科学“十一五”规划课题(D/2009/01/068);江苏省教育厅高校哲学社会科学研究项目(09SJD630045)
更新日期/Last Update: 2012-10-12