Prediction of firing accuracy of self-propelled antiaircraft gun in marching fire based on GA-BP neural network

Abstract The firing efficiency during the marching fire is an important indicator to measure combat of self-propelled antiaircraft gun, and it very improve accuracy fire. In order understand coupling mechanism between density various influencing factors anti-aircraft guns, this paper combines different driving shooting conditions study such as speed, road grade, load, angle other factors. A method predicting guns proposed based on GA-BP neural network. This not only provides a theoretical basis indirect measurement for quantification marching, but also has significance distribution design guns.