Clock error prediction method and device based on deep learning, medium and terminal

The invention discloses a clock correction prediction method and device based on deep learning, a medium and a terminal. The method comprises the steps: obtaining a target time sequence which is the time sequence of to-be-predicted clock correction data; inputting the target time sequence into a pre-trained clock error prediction model; wherein the clock error prediction model is obtained by training by taking a sample time sequence in a training sample as input data and taking a sample clock error sequence as supervision data of output data; and taking data output by the clock correction prediction model as a clock correction prediction result. By adopting the scheme, the accuracy of clock error data prediction can be improved. 本申请公开了一种基于深度学习的钟差预测方法、装置、介质及终端，该方法包括：获取目标时间序列，所述目标时间序列为待预测钟差数据的时间序列；将所述目标时间序列输入至预先训练得到的钟差预测模型；其中，所述钟差预测模型是以训练样本中的样本时间序列作为输入数据，并以样本钟差序列作为输出数据的监督数据，来进行训练得到的；将所述钟差预测模型输出的数据作为钟差预测结果。通过采用本方案，可以提高钟差数据预测的准确性。