التفاصيل البيبلوغرافية
| العنوان: |
基于 Bahdanau 注意力机制的大口径火炮 双向 GRU轨迹预测. (Chinese) |
| Alternate Title: |
Bidirectional GRU trajectory prediction for large-caliber artillery based on bahdanau attention mechanism. (English) |
| المؤلفون: |
彭晨洋, 陈龙森, 张鸣洋 |
| المصدر: |
Journal of Ordnance Equipment Engineering; 2024, Vol. 45 Issue 7, p56-64, 9p |
| Abstract (English): |
In response to the trajectory prediction problem of large-caliber artillery projectiles, a sequence- to-sequence trajectory prediction model (S2S ATT-BiGRU) based on the Bahdanau attention mechanism and bidirectional gated recurrent unit network is proposed. A large number of projectile trajectory data samples are obtained through the simulation of the 6-degree-of-freedom projectile motion model under different conditions, and the simulated dataset is constructed using the sliding window method and difference method. The proposed trajectory prediction model is compared with GRU model through simulation experiments on the simulated dataset. The research results show that the S2S ATT-BIGRU model, when predicting the future time of 5 s based on an input time of 0.5s, has an MSE of 13.89 m², an MAE of 1.84 m, and an MAPE of 0.29%, which is significantly more accurate than GRU model. In most cases, the S2S ATT-BiGRU model s predictions are superior to GRU model. These findings suggest that the S2S ATT-BiGRU model has a stronger ability to store input trajectory sequence information and adaptively focus on important input trajectory information, providing a favorable reference for projectile trajectory prediction research [ABSTRACT FROM AUTHOR] |
| Abstract (Chinese): |
针对大口径火炮弹丸轨迹预测问题, 提出一种基于Bahdanau 注意力机制与双向门控循环单元网络的序列到序 列轨迹预测模型 (S2S ATT-BiGRU). 通过不同条件下六自由度弹丸运动模型仿真, 得到大量弹丸轨迹数据样本, 并 利用滑动窗口法和差分法构造仿真数据集;将所提轨迹预测模型与 GRU 模型在仿真数据集下进行实验. 研究结果 表明, S2S ATT-BiGRU 模型在输入时间为0.5s预测未来时间为 5s 的情况下, 其MSE为13.89m², MAE为1.84m, MAPE为 0.29%, 其预测精度远高于 GRU 模型. 在其余情况下S2S ATT-BiGRU 模型的预测结果均优于GRU 模型. 这表明 S2S ATT-BiGRU 模型具有更强的存储输入轨迹序列信息和自适应关注重要输入轨迹信息的能力, 为弹丸轨 迹预测研究提供有利参考. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
