【摘要】 为了侦破采用信息技术手段的犯罪活动,需要强大的计算机智能系统。为此,提出一种利用神经网络,对银行客户潜在洗钱风险进行分类的方法,作为完整系统的部分支持。利用主元分析确定最合适的数据集,依靠L-M和贝叶斯正则化方法来训练最优效果的网络。实验结果表明,神经网络在解决目标问题的过程中比较有效。更多还原

【Abstract】 Computer intelligent system is needed to crack crime activities using information technologies.This paper proposes a study aiming at constructing an effective anti money laundering system together with other respectable researches.A precise mode of BP network is constructed to evaluate the potential risk of money laundering of a certain bank account.Principle components analysis gives an inside view of data structure helping to find better input form for network.Levenberg-Marquardt algorithm accelerates the training process of BP impressively.And on the way generalization Bayesian regularization proves its value.Experimental result of the final system is satisfactory.更多还原