NEURAL NETWORKS:
MUZZLE VELOCITY PREDICTION

Based on a military requirement Decilog has developed a Recurrent Neural Network for use in predicting muzzle velocities for artillery weapon systems. Muzzle velocity predictions are based on measured MVs of prior rounds as well as on a variety of round, propellant, and weapon state parameters. The Recurrent Neural Network is shown to be an ideal architecture for time series predictions.