Abstract: Agricultural produces price forecasting is one of the main research issues in the field of agricultural economy, and it is of great interest to many researchers and institutions.A novel method is proposed in this paper for agricultural produces price forecasting based on Ensemble Empirical Mode Decomposition (EEMD) method and Long Short-Term Memory (LSTM) network. First, the original price series is decomposed by EEMD to several IMF subsequences and one residual sequence. Then, the fine-to-coarse method is used to reconstruct the IMF subsequences into high frequency item and low frequency item. Finally, the original price series, high frequency item, low-frequency item and residual sequence are taken as input features to train the LSTM network, so as to construct an EEMD-LSTM combined forecasting model.

Key words: agricultural produces; short-term price forecast; ensemble empirical mode decomposition; long short-term memory