基于ARIMA-LSTM模型的GNSS高程时间序列预测
Prediction of GNSS Elevation Time Series Based on ARIMA-LSTM Model
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摘要: 针对ARIMA和LSTM单一模型预测GNSS高程时间序列存在精度较低的问题, 提出用ARIMA-LSTM混合模型预测GNSS高程时间序列。分析了ARIMA-LSTM模型的基本原理, 探讨了模型的建立与数据处理方法, 并通过实验对其预测结果进行验证。实验结果表明, 在GNSS高程时间序列预测中, 相比于ARIMA和LSTM任何一个单一模型, ARIMA-LSTM模型表现出更高的预测精度和鲁棒性。Abstract: In view of the problem of low accuracy in predicting GNSS elevation time series using either the single ARIMA or LSTM model, an ARIMA-LSTM hybrid model is proposed for predicting GNSS elevation time series. The fundamental principle of the ARIMA-LSTM model is analyzed, the establishment and data processing of the model are discussed, and its prediction results are verified through experiments. The experimental results show that in the prediction of GNSS elevation time series, the ARIMA-LSTM model exhibits higher prediction accuracy and robustness compared to either the ARIMA or LSTM model individually.