How to use extrapolation to predict the future data

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Sara
Sara on 1 Sep 2020
Commented: Sara on 2 Sep 2020
Hello,
I have a dataset of degradation of different systems. Normally a system degrades when its health reaches 80% of its initial value.
However, as you can see in the picture, many of these systems have not reached 80% due to time limitations.
My question is How can I use extrapolation to expand my data until they reach 80%. attached you can find my data set. Each row of the cell shows the degradation of a system
I appreciate any help.

Accepted Answer

Abdolkarim Mohammadi
Abdolkarim Mohammadi on 1 Sep 2020
Edited: Abdolkarim Mohammadi on 1 Sep 2020
You should find a mathematical model a model to each of your lines using curve fitting toolbox. Type cftool in the command window to open the app. Generally, you first find a good model visually, and then validate it. Please read the post processing documentation: https://www.mathworks.com/help/curvefit/fit-postprocessing.html
I have fitted the first variable (SOH{1} vs. cycle{1}) and it seems that an exponential function of the second order can be a suitable fit, since the fitted curve is very close to the data points and I have got tight confidence bounds for each parameter.
The histogram plot of residuals also show that the follow a symmetric Normal distribution, which is another sign of a good fit.
After you achieved a good model for each of your lines, you can use fit functions to evaluate it for points outside the data points, i.e., extrapolation.
There is a caveat with extrapolation, that your actual system might have a different behavior in regions that have not been sampled. Extrapolation assumes that your system behaves similarly inside and outside of the sampled data.
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