Exception Detection for ATM Transaction Status Based on a Self-Organizing Feature Mapping Model

摘要

In order to solve these problems such as monitoring the ATM behavior of operation, exception detection for ATM transaction status and so on, in this paper we establish the detecting system of SOFM for the ATM to raise the timely alarm and reduce the false alarm rate. The results of SOFM model simulation show that the ATM transaction exceptions collected in data base can be timely and accurately detected and the false alarm rate is low. The model has high classification accuracy, which verifies its effectiveness.