AN EARLY WARNING SYSTEM BASED ON FUZZY CMAC

摘要：

Many statistical models such as the Coxs model have been applied to the study of bank failure.However, these classical models have not attempted to identify the possible traits of financial distress that eventually leads to bank failure.It is difficult to explicitly specify what constitutes a financial distress and the intrinsic relationship between financial distress and a failed bank.This paper attempts to apply a fuzzy system named FCMAC-TVR to bank failure analysis.The FCMAC-TVR network is a generic network, in which the numerical operation is carried out by neural network, but the readable rules are generated by TVR inference scheme.The trained FCMAC-TVR operates as a bank failure classification and prediction system and the formulated fuzzy rule base shed lights on the inherent contributions of the selected financial covariates to bank failure.Experiments have demonstrated that the FCMAC-TVR network consistently outperforms the Coxs model in classifying failed and survived banks using a set of US banking data.

关键词： Early warning system Fuzzy CMAC

作者: JIA-CAI FU JUAN SHI MINH NHUT NGUYEN

作者单位: Heilongjiang Institute of Science and Technology, Harbin, China School of Computer Engineering, Nanyang Technological University, Singapore 639798

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 156-159

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）