Notice of RetractionBlade optimization of Multiphase Rotodynamic pump based on neural network 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.

A new method based on neural network and genetic algorithm to optimizate the Multiphase Rotodynamic pump is given. Using cubic B-spline surface to parametric the blade profile. Based on the ability of highly nonlinear fitting of BP neural network, the nonlinear relation between the blade parameter and the pump performance parameters is build. Let the trained neural network as a fitness function of the genetic algorithm, using the characteristic of nonlinear global optimization of genetic algorithms to optimize multiphase rotodynamic pump. Through the fluent numerical calculation of the genetic algorithms output value, the results show that the capability of multiphase pump blade is improved, and then proved the feasibility of the optimization method.