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供应链需求的预测方法,大致归为两类:一类是单一预测方法,如采用神经网络预方法、灰色预测法、马尔可夫预测法、时间序列预测方法、基于价值量的预测方法等;另一类是组合预测方法,即利用多预测方法的预测结果按一定方式进行组合。另外也有学者提出了别的方法,如情景分析法、集对分析聚类预测等等。本文只对作者所研究过的方法,进行总结和归纳。
Supply chain demand forecasting methods are broadly classified into two categories: one is a single forecasting method, such as the use of neural network pre-method, gray forecasting method, Markov forecasting method, time series forecasting method, value-based forecasting method, etc. One is the combination forecasting method, which uses the forecasting result of multi-forecasting method to combine according to a certain way. In addition, some scholars have proposed other methods, such as scenario analysis, set pair analysis clustering prediction and so on. This article only summarizes and summarizes the methods studied by the author.