Abstract
In this paper, an optimization system is established based on a hybrid neural network and genetic algorithm approach. The application program is compiled in Matlab engineering computing language, which is used in calculating the parameter value predicted by neural network and the result of genetic algorithm optimization. The comparison and error analysis has been carried out between the results predicted by network and CAE simulated results, which shows that the BP network is stable and reliable. The optimized outcome verified by CAE simulation and tested by experiment has been proved to be correct. It has been bean indicated that the injection parameter optimization method based on the hybrid neural network and genetic algorithm approach is feasible.
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