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This answer explained steps to building time series model for forecasting. However, the model is used for one-step ahead. How can I perform multi-step ahead?

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I'm not an expert on MLP time series models, but logically there are two ways you can do this. These examples asume you want to skip 2 steps, and the trainingset is x1, x2, x3, xn...

Method 1, teach to skip months:

You should train your network as follows:

Input: [x1, x2, x3], Output: [x6]

You basically just teach it the pattern between xn, xn+1, xn+2 and xn+5.

Method 2, predict multiple months

This advise is more eye-appealing, but it requires more steps:

Input: [x1, x2, x3], Output: [x4] -> save x4 to next step

Input: [x2, x3, x4], Output: [x5] -> save x5 to next step

Input: [x3, x4, x5], Output: [x6] -> you have your output

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