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Building a time series predictive model using machine learning or deep learning for, intermittently sampled, vehicle diagnostic data

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Farouk Balouchi
Farouk Balouchi on 9 Aug 2019
Answered: Dheeraj Singh on 10 Sep 2019
I’m relatively new to machine learning and deep learning subjects but have experience in matlab programming. I’m looking for a fundamental method of predicting the occurance of diagnostic data from a complex vehicle system such as a plane or train. Diagnostic data is recorded when an event with a particular code is triggered; that code then retrieves a set of environment variables such as speed, pressure, temperature etc. The data is sampled only when an event it triggered so the sampling, more often then not, does not have a constant frequency. I have data that tells me that the accumulation of an event and its environment variable leads to a maintenance action. Any pointers towards building a predictive model would be nice. Thanks Faz.


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