Considering many nonlinear and unquantifiable uncertainties influencing the demand of automobile parts in 3 PL warehouse, an integrated forecasting model, the SIF(synthetic integrated forecasting) model, is proposed, which combines quantitative and qualitative models. In the SIF model proposed, the RBF(radial basis function) neural networks(RBF NN) predict the complex nonlinear trend of demand. For some difficulties in establishing the RBF NN, the autoregressive integrated moving average model(ARIMA) model ...
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