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应用科学学报 ›› 2003, Vol. 21 ›› Issue (2): 209-213.

• 论文 • 上一篇    下一篇

一种基于粗集神经网络的欺诈风险分析方法

盛昭瀚1, 柳炳祥2   

  1. 1 南京大学管理科学与工程研究院 江苏 南京 210093;
    2 东南大学经济管理学院 江苏 南京 210096
  • 收稿日期:2002-06-07 修回日期:2002-09-17 出版日期:2003-06-10 发布日期:2003-06-10
  • 作者简介:盛昭瀚(1944-),男,江苏镇江人,教授,博导.
  • 基金资助:
    国家自然科学基金(70171028)

A Method Based on the Rough Neural Network for Analysing Deception Risks

SHENG Zhao-han1, LIU Bing-xiang2   

  1. 1 Institute of Management Science and Engineering, Nanjing University, Nanjing 210093, China;
    2 Institute of Economics and Management, Southeast University, Nanjing 210096, China
  • Received:2002-06-07 Revised:2002-09-17 Online:2003-06-10 Published:2003-06-10

PDF

91

被引次数

32

摘要： 指出了传统的欺诈风险分析模型存在的问题,提出了一种基于粗集神经网络的欺诈风险分析方法.详细叙述了粗集神经网络的基本原理及基于粗集神经网络的欺诈风险分析方法,并给出了一个基于粗集神经网络的信用卡欺诈的分析实例。实验结果表明,该方法应用于欺诈风险的分析中是有效的,为欺诈风险的分析和预警提供了一条新的研究思路和方法。

关键词: 风险, 神经网络, 预警, 粗集, 欺诈风险

Abstract: This paper states the basic concept of deception and analyses the causes that give rise to the risk of deception. The methods of identification, analyzing and estimation of deception risks are discussed. The shortcomings of the traditional models for evaluating deception are also discussed. A method based on the rough neural network for analyzing deception risks is suggested and an example is given to validate the algorithm. The results show the feasibility and validity of the method. The research work furnishes a basis for further study of applying rough neural network to the analysis and prediction of deception risks.

Key words: risks, rough set, neural network, predicting, deception risks

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