Notice of RetractionApplication of genetic algorithm-RBF neural network in water environment risk 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.

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Water environment risk prediction is significant to improve utilization efficiency of water resource. In the study, genetic algorithm-RBF neural network is applied to water environment risk prediction, where RBF neural network has very good nolinear forecasting ability, and genetic algorithm is used to select the parameters of RBF neural network. The four indices of water environment include gross amount of water resources, per capita water resources, total volume of water consumption and total amount of discharge for wastewaters. The future water environment risk situation can be gained by forecasting for the four indices. The water environment data from 2000 to 2006 in China are adopted as our experimental data. The experimental results indicate that the forecasting results of the four indices of water environment of GA-RBFNN are better than grey model.