Notice of RetractionPrediction of regional economies based on the hybrid method of support vector machine and genetic algorithm

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.

In order to solve the problems of high nonlinearity of regional social systems, the hybrid method of support vector machine and genetic algorithm is applied to predict regional economies. Support vector machine is a statistical learning procedure based on the structural risk minimization principle, which has very strong nonlinear regression. Genetic algorithm is well-known as an more widely used method, which is applied to select the operating parameters of support vector machine. The regional economies data from 1987 to 2003 are used to verify the effectiveness of the proposed approach. It is observed from the experiments that prediction performance of the proposed approach than that of normal support vector machine. It is concluded that the proposed approach is a viable alternative to predict regional economies.