Long Time Series Prediction of Meteorological Data Based on Improved Autoformer Model

Aiming at the problem of low prediction accuracy caused by many uncertain factors in the prediction of long-time series of meteorological data, a long-time series prediction model of meteorological data based on improved Autoformer model (Wdformer) is proposed. Change the routine of sequence decomposition pretreatment and reduce the noise and irregularity in the data by introducing dynamic diffusion to simulate the changes of meteorological elements in the atmosphere; The wavelet transform time series decomposition module is designed to improve the gradual decomposition ability of the model for long time series. The experimental results of meteorological data prediction in a certain area show that the accuracy of the proposed Wdformer model is higher than that of the standard Autoformer model.