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Title of the item:

Research on duplicate combined forecasting method based on supply chain coordination.

Title :
Research on duplicate combined forecasting method based on supply chain coordination.
Authors :
Zhu, Yanxin
Li, Sujian
Peng, Yongfang
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Subject Terms :
AGRICULTURAL forecasts
SUPPLY chains
ARTIFICIAL neural networks
FARM supplies
SCIENTIFIC method
Source :
Cluster Computing; May2019 Supplement 3, Vol. 22, p6621-6632, 12p
Academic Journal
The coordinated forecast of agricultural means supply chain not only needs cooperation and information sharing among different parties but also needs scientific forecast methods and means. This paper firstly builds the synergetic framework of demand forecast and analyzes the key factors of demand forecast coordination in different forecast stages and then confirms duplicate combined forecast method for time series based on the factors which influence the demand of agricultural means. GM(1,1) is used in the model to forecast the fluctuant items of long-term trend; BP neural network and ARMA are used to simulate periodically fluctuant items. Particle swarm algorithm is used to confirm the combined forecast model of periodically fluctuant items. Finally, a calculating example is used to compare the forecast precision of the combined forecast model, GM(1,1), BP neural network model and ARMA model. In conclusion, duplicate combined forecast model is applicable to forecasting the demand of agricultural means which are influenced by long-term trend and periodically fluctuant factors. [ABSTRACT FROM AUTHOR]
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