Artificial Neural Network Technology on Computational Finance Application

摘要：

the different capital configurations of bank accounts for different credit tendency which will affect the currency condition as well as whole finance system．The mercurial and nonlinear factors of economy usually brought the difficulty when predicts．This study adopts the feed-forward backprop network (BP)，conceiving predicting modeling with the sample of various banks’．The simulation results indicated that the model performs well in anti-interference and accurate in prediction error(less than 2％)．Moreover,we got the result that non state-own banks tend to be more cautious than state-own by 10％on average．

关键词： Credit tendency difierence Artificial Neural Networks(Ann) Anti-interference prediction．

作者: XIA Huo-Song CWANG Yi LIU Jian

作者单位: Department of economics and management,Business Intelligence and Data Mining Lab．Wuhan Textile Unive Department of economics and management,Business Intelligence and Data Mining Lab.Wuhan Textile Unive Department of economics and management Wuhan Textile University．Wuhan．P．R．C.

会议类型: 国际会议

会议名称: The First International Conference on Complexity Science Management(2010 计算机与软件建模国际会议 ICCSM2010)

会议地点: 武汉

会议语种:英文

页码: 54-60

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）