The existing recurrent neural networks are subject to training overfitting,low prediction accuracy,poor generalization ability,and weak adaptability in solving target trajectory prediction.A target trajectory prediction method using an improved attention mechanism and Gated Recurrent Unit(GRU)was proposed,which could automatically terminate the network training process through an early stopping method to prevent overfitting during training.It saved the optimal network parameters during network training through the model checkpoint function.By introducing an attention mechanism into the GRU network and assigning different weights to trajectory features to focus on key trajectory information,the predictive performance of the network was optimized Finally,simulation experiments results show that the proposed method effectively improves the prediction accuracy,generalization,and adaptability of recurrent neural networks.
trajectory predictionattention mechanismearly stop methodrecurrent neural networkgated recurrent unit
国家科技期刊平台
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