BiGRU Battlefield Target Intention Discrimination Based on Attention Mechanism
Aiming at the complexity and diversity of modern battlefield environment information and the hidden and deceptive battlefield targets,a battlefield target intention recognition method based on bidirectional gated cyclic u-nit(BiGRU)was proposed.In order to make the network pay more attention to the key points of information and im-prove the accuracy of target intention recognition,an attention mechanism was added into BiGRU.The attention mech-anism can make the model pay more attention to the parts closely related to the prediction results and ignore the places with low correlation.Moreover,Zoneout mechanism was adopted to reduce the network overfitting.The experi-mental results show that the accuracy of BiGRU method combined with attention mechanism is up to 97.1%,which is 12%higher than that of the basic GRU algorithm.
Attention mechanismBattlefield targetsIntention of discriminant
NETL
NSTL
万方数据
