基于季节分解与曲线拟合的物流量预测混合模型

A Mixed Model of Material Flow Forecasting Based on Seasonal Decomposition and Curve Fitting

针对时间序列预测与曲线拟合预测的优缺点,提出了一种季节分解与曲线拟合相结合的混合预测模型,解决了曲线拟合精度与高阶次震荡性强的矛盾,提高预测的精度和模型对数据的适应能力。同时针对具有时间周期特性的物流量,该模型在预测时充分考虑了上期物流量及近期预测物流量对本期的影响。最后将该模型与其他预测方法相比较,证明该模型的有效性和可行性。

In view of the advantages and disadvantages of time series prediction and curve fitting prediction,a hybrid prediction model combining seasonal decomposition and curve fitting is proposed,which solves the contradiction between curve fitting accuracy and high-order oscillation,and improves the prediction accuracy and the adaptability of the model to data.At the same time,for the logistics volume with time-periodic characteristics,the model takes full account of the impact of the previous logistics volume and the recent forecast logistics volume on the current period.Finally,the model is compared with other prediction methods to prove the validity and feasibility of the model.