基于遥感和深度学习的输电线路地表水深预测

张可, 张庚生, 王宁, 温静, 李宇, 杨俊

A forecasting method for water table depths in areas with power transmission lines based on remote sensing and deep learning models

ZHANG Ke, ZHANG Gengsheng, WANG Ning, WEN Jing, LI Yu, YANG Jun

表2 LSTM、GRU和LSTM-S2S模型中月度数据的性能

Tab.2 Performance statistics of monthly data in LSTM, GRU, and LSTM-S2S models

模型 均方根误差 决定系数 效率系数 损失 LSTM 1.04 0.65 0.60 15.21 GRU 0.83 0.75 0.74 23.58 LSTM-S2S 0.89 0.71 0.71 4.70