基于DNGM(1,1)模型的农产品物流需求预测

Demand Forecast of Agricultural Products Logistics Based on DNGM(1,1)Model

农产品物流是城市民生的重要保障,建立精确合理的农产品物流需求预测模型是合理规划城市物流资源的重要依据.以北京市农产品物流需求为研究对象,选择适用于小样本数据的灰色模型进行预测,并在传统模型的基础上进行了改进,经过不断尝试,最终采用DNGM(1,1)预测模型,结合使用MATLAB2019b软件,并与优化的GM(1,1)模型和GM(1,n)模型结果进行对比分析.结果表明,DNGM(1,1)预测模型的拟合和预测精度优于其他的两个预测模型,弥补了传统预测模型的不足,是预测农产品物流需求更为有效的研究方法,并以此为政府决策提供数据支撑.

Agricultural product logistics is an important guarantee for urban people’s livelihood.Establishing an accurate and reasonable forecast model for agricultural product logistics demand is an important basis for rational planning of urban logistics resources.This paper takes the logistics demand of agricultural products in Beijing as the research object,selects a gray model suitable for small sample data to predict,and improves on the basis of the traditional model.After continuous attempts,the DNGM(1,1) prediction model is finally adopted.Combine the MATLAB2019 b software,and compare and analyze the optimized GM(1,1) model and GM(1,n) model results.The results show that the fitting and prediction accuracy of the DNGM(1,1) forecasting model is better than the other two forecasting models,which makes up for the shortcomings of the traditional forecasting model.It is a more effective research method for forecasting the logistics demand of agricultural products.Government decision-making provides data support.