基于EEMD-ARMA模型的我国木材产量预测

Prediction of Wood Production Based on EEMD-ARMA

运用EEMD分解和ARMA模型相结合对我国木材产量进行了预测。首先利用EEMD技术对原始信号进行分解,得到频率单一、平稳的本征模函数和光滑的趋势余波,然后运用ARMA模型分别对本征模函数和余波进行预测,最后将二者预测值合并,实现对目标的精确预测。结果显示:EEMD-ARMA模型的平均预测误差为2.1169%,比ARMA模型的平均预测误差3.0018%减小29.4586%。由EEMD-ARMA模型预测得到2021年我国木材产量为10677.51万米立方米。

Combining EEMD decomposition and ARMA model,the wood production in China is predicted.Firstly,EEMD technology is used to decompose the original signal to obtain the single frequency and stable eigenmode function and smooth trend residual wave.Then ARMA model is used to predict the eigenmode function and residual wave respectively.Finally,the predicted values of the two are combined to realize the accurate prediction of the target.The results shows that the average prediction error of EEMD-ARMAmodel is 2.11689%,which is 29.45862%%lower than that of ARMA model.The EEMD-ARMA model predicts that the woodproduction in China will be 106.7751 million m3 in 2021.