Hi Glen, This is actually something I know a little about.
Neural nets are most useful for feature selection, that is, finding the important x that is a function of y, in a very large sea of x variables. In this case, we already know what's important, which is temperature stability. So, a neural net would be a bit much when we already know what feature is important for function. Additionally, unless I'm mistaken, oven control is probably a linear relationship of some sort or another, and neural nets are much better suited for examining and revealing insights about non-linear data. If you have a method by which you can collect the necessary data that has a bearing on the oven functionality, you'd probably be better off training a logistic classifier, and using it instead. That said, both methods would be overkill, imo- I'd use a PID instead. Best, Chase On Tue, Jul 9, 2019 at 10:00 PM Glen English VK1XX < [email protected]> wrote: > Has anyone tried to use a Neural net to control oven tmep, rather than > the ye olde PID ? > > IE the algorithm learns from previous beheviour and successfully > predicts behaviour (or not). > > I'm sure there are a few out there proficient with machine learning > algorithms. > > Might make a good masters thesis I bet. > > Given that oven control based on inputs and whatever is not random, > unlike say flicker etc. > > glen > > > > _______________________________________________ > time-nuts mailing list -- [email protected] > To unsubscribe, go to > http://lists.febo.com/mailman/listinfo/time-nuts_lists.febo.com > and follow the instructions there. > _______________________________________________ time-nuts mailing list -- [email protected] To unsubscribe, go to http://lists.febo.com/mailman/listinfo/time-nuts_lists.febo.com and follow the instructions there.
