A new study has developed a two-level satellite timing system using a sparse sampling Long Short-Term Memory (LSTM) algorithm. This innovative approach significantly boosts the autonomous time-keeping ...

本文推荐研究人员针对传统计量模型在复杂金融时序预测中的局限性，开展了深度学习模型(LSTM、Transformer)与经典方法(ARIMA ...

Demand forecasting remains one of the most complex challenges in retail management. As consumer behavior evolves rapidly, traditional statistical models have struggled to interpret nonlinear, dynamic ...

本文提出了一种创新的CBAM-LSTM-Attention混合模型，通过XGBoost算法优化EEG通道选择，显著提升了情绪识别的准确率与计算效率。该模型融合通道-空间注意力模块（CBAM）与多头时间注意力机制，在DEAP数据集上单通道分类唤醒度（arousal）和效价（valence）分别达95.108% ...

Beijing, Jan. 22, 2024 (GLOBE NEWSWIRE) -- WiMi Hologram Cloud Inc. (WIMI) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced an ...

According to the analysis, deep learning architectures such as Long Short-Term Memory (LSTM) networks and hybrid CNN-LSTM ...