北平原区通过MT-InSAR提取2017-2022年地变形时序数据，结合SHAP可解释机器学习模型识别出地下水储量变化、年降水量和道路密度是主要驱动因素，并构建了融合动态时序数据、静态参数和空间信息的CMI-LSTM模型，预测精度显著提升。 摘要 在全球极端气候事件、农业 ...

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...