Neural network mixed model for profile modeling spray of fruit trees based on GA

The relationship among the parameters for profile modeling spray of fruit trees based on BP neural network shows that BP neural network cannot avoid instability and local infinitesimal. In order to overcome the localization of BP neural network, in which can not avoid instability and local infinitesimal, GA was used to optimize the weight coefficient, and a model combining BP with GA was set up. The result shows that, the accuracy of the mixed model is higher than the BP model, the average relative error falls down from 0.05 to 0.019, and mean square error down from 0.005 to 0.002; during the forecast, the relative error cuts down, and the eligible rate boosts from 60% to 80%. The mixed model can solve the instability which the simple model has, and avoid the disadvantage of local infinitesimal.