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I can't decide which model fits perfectly for these tasks:

Time:05-23

enter image description here Predict what the condition of these trucks will be in 2020.

  • Predict when (i.e. after how many years) each truck will reach the condition 2.

CodePudding user response:

Predict what the condition of these trucks will be in 2020

  • You should probably start by looking at the data and afterwards start simple. Instead of trying LSTMs on these kind of datasets, try to fit some standard regression models and look at the general errors you get.

Predict when (i.e. after how many years) each truck will reach the condition 2

  • I can't see the data myself, but I think you will have to extrapolate in a way to find a kind of answer on this question. If you only have datapoints from 2010 up to 2019 and most of the trucks' conditions go from 10 to circa min 8 or 7 in these years, you could calculate what the average degeneration is over all trucks for this timespan and use it to find, on average, how many years it cost to degenerate 1 condition and extrapolate this up to condition 2 for a given truck with a given condition.
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