IGM(1,1)-TFN 模型在产品回收预测的应用

Application of IGM(1,1)-TFN model in the forecasting of returns

中文关键词  关产品回收预测  逆向物流  传递函数  白噪声  自相关  互相关

英文关键词  forecasting returns  reverse logistics  transfer function  white noise  autocorrelation  cross correlation

中文摘要

      针对现有回收预测模型数据需求量大和适用范围窄的不足, 提出了改进GM(1,1)－传递函数噪声两阶段预测模型. 回收初期数据缺乏, 采用改进邻域系生成方法的GM(1,1)模型, 实现了少量数据情况下的预测; 回收数据累积到50 个后, 利用传递函数噪声模型构建了回收量和前期销售量之间的内在数量关系式, 然后通过模型识别、参数估计、诊断检验确定了关系式的具体参数, 进而实现了回收预测. 最后通过一个实例验证了模型的合理性和有效性.

英文摘要

      To overcome the disadvantages of the current forecasting returns models, such as narrow application extent and requirement for more data, an improved GM(1,1)-transfer function-noise model is proposed in this paper. For the lack of return data in the first stage, the GM(1,1) model improving the generation method of neighborhood system is adopted, and forecasting is carried out by only using a few data. When data amounts reached to 50, the hidden quantitative relationship between sale quantity and return quantity is established by performing the transfer function-noise model. Its parameters are determined through model identification, parameters estimation and diagnostic checking. Then, forecasting return is accomplished. Finally, an example is provided to verify the rationalities and efficiencies of the model.