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基于Levenberg-Marquardt神经网络的企业资信评估方法研究
引用本文:蔡秋茹,柳益君,蒋红芬,罗烨,叶飞跃.基于Levenberg-Marquardt神经网络的企业资信评估方法研究[J].计算机与数字工程,2009,37(7):154-156,180.
作者姓名:蔡秋茹  柳益君  蒋红芬  罗烨  叶飞跃
作者单位:江苏技术师范学院计算机科学与工程学院,常州,213001
基金项目:常州市"831工程"资助项目,江苏技术师范学院基金重点资助项目 
摘    要:企业资信评估问题是一个复杂的非线性问题,而神经网络技术可实现非线性关系的隐式表达。文章提出将基于Levenberg-Marquardt算法的多层前馈型神经网络用于资信评估,并通过MATLAB软件及其神经网络工具对其进行仿真计算。实验结果表明,企业资信神经网络评估模型收敛速度快,准确率较高,具有一定的实用价值。

关 键 词:神经网络  Levenberg-Marquardt算法  资信评估

Corporation Credit Rating with Neural Network Based on Levenberg-Marquardt Algorithm
Cai Qiuru,Liu Yijun,Jiang Hongfen,Luo Ye,Ye Feiyue.Corporation Credit Rating with Neural Network Based on Levenberg-Marquardt Algorithm[J].Computer and Digital Engineering,2009,37(7):154-156,180.
Authors:Cai Qiuru  Liu Yijun  Jiang Hongfen  Luo Ye  Ye Feiyue
Affiliation:School of Computer Sciences and Engineering;Jiangsu Teachers University of Technology;Changzhou 213001
Abstract:Corporation credit rating is a complex nonlinear problem.It has become a hot topic in the application of neural networks to solute the problem of corporation credit rating.In this study,the neural network based on Levenberg-Marquardt algorithm is applied to the problem.Matlab software and its neural network toolbox are used to make network compute.The experiment results show that the neural network model is effective and efficient.
Keywords:neural network  levenberg-marquardt algorithm  credit rating  
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