I have a very specific problem where I am trying to forecast tomorrow's electricity price with an hourly resolution (from tomorrow at midnight to tomorrow at 11pm). I need to forecast prices before 10AM today. Electricity prices have very strong seasonality (24 hours) and I am using the whole day of yesterday and today up to 10AM as an input to the model (an input of 34 hours). In tensorflow terms (https://www.tensorflow.org/tutorials/structured_data/time_series) my input width is 34, the offset is 14 and the label width is 24.
Since I only care about the predictions I get at 10AM for the following day, should I only train my model with the observations available at 10am?
I am pretty sure this has been addressed before. Any documentation/resources that consider similar problems would help
OnlyAnalyst9642 t1_jdxlki8 wrote
Reply to [D] Simple Questions Thread by AutoModerator
I have a very specific problem where I am trying to forecast tomorrow's electricity price with an hourly resolution (from tomorrow at midnight to tomorrow at 11pm). I need to forecast prices before 10AM today. Electricity prices have very strong seasonality (24 hours) and I am using the whole day of yesterday and today up to 10AM as an input to the model (an input of 34 hours). In tensorflow terms (https://www.tensorflow.org/tutorials/structured_data/time_series) my input width is 34, the offset is 14 and the label width is 24.
Since I only care about the predictions I get at 10AM for the following day, should I only train my model with the observations available at 10am?
I am pretty sure this has been addressed before. Any documentation/resources that consider similar problems would help
Thanks in advance!