Notice of RetractionThe application of genetic-neural network on the evaluation about the college student´s personal credit situation

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.

State student assistance loan is a personal credit loan, but the personal credit evaluation system of commercial banks could not make a correct assessment for a college student´s credit situation because the students have no records about their credit. To avoid the credit risk, it must to establish a rational credit evaluation methodology for college students. As a result of traditional neural network algorithm existing shortcomings that are training time to be long, the convergence rate slow and easy to fall into the partial minimum point, a method of fusing genetic algorithm and neural network control is proposed in this article. The model adopts neural network structure,genetic algorithm is used to optimize the attached weights and thresholds of neural network. 16 samples are used for network training and testing by MATLAB. Simulation results demonstrate that BP neural network exists the phenomenon of failed prediction, but genetic-neural network model all predicts correctly and the maximum value of error about the model output and target output is only 3.2%, therefore using genetic-neural network carry on the college student´s personal credit evaluation is method that has a better effect than using BP neural network only.