Notice of RetractionA methodologic application of Customer Retention based on back propagation Neural Network prediction

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

Unprecedented growth of competition has raised the importance of retaining current customers. Retaining existing customers is much less expensive and difficult than recruiting new customers in a mature market. So customer retention is a significant stage in Customer Relation Management, which is also the most important growth point of profit. But the customer information is always nonlinear, so the traditional statistic and econometric methods are limited. Neural Network prediction is drawn into customer retention and case is utilized to test the simulation situation. The results show that the system training accuracy is 0.000910 and the simulation is excellent, which has assured the robustness and applicability. More modeling attempt is to be done to reduce training times and improve training efficiency in further work.