how to predict future values?

1 view (last 30 days)
navid zed
navid zed on 8 Dec 2016
Commented: navid zed on 11 Dec 2016
hi there,I have been working on my thesis that is related prediction the land surface temperature. I want predict it with neural network,thus I downloaded images of 10 years from 1985 to 2014. I set the LST(land surface temperature) as target and some indices as inputs. however I can train the network with neural network toolbox,I do not know how to predict the LST of future years,for instance 2017. I will be thankful,if you help me. thanks

Accepted Answer

Greg Heath
Greg Heath on 10 Dec 2016
Edited: Greg Heath on 10 Dec 2016
If you need to predict 3 years ahead, then you should practice on data spaced 3 years apart.
The autocorrelation function of the target and the cross-correlation function of the target and input will yield the significant predictive spacings between the current output with past outputs and the current input.
There are many helpful posts and examples in the NEWSGROUP and ANSWERS. Try searching in both with
greg nncorr narxnet
Hope this helps.
Thank you for formally accepting my answer
Greg
  1 Comment
navid zed
navid zed on 11 Dec 2016
hi Greg, thanks for answering me, I didn't understand what you meant. let me clarify my question. I have downloaded images of 10 years(1985,1990,1994,2000,2002,2005,2008,2010,2012,2014). I clipped images, retrieved LST and other indices and put it in input and output like this: inputs = [{[albedo85;NDVI85;IBI85;NDISI85]},{[albedo90;NDVI90;IBI90;NDISI90]},... {[albedo94;NDVI94;IBI94;NDISI94]},{[albedo2000;NDVI2000;IBI2000;NDISI2000]},... {[albedo2002;NDVI2002;IBI2002;NDISI2002]},{[albedo2005;NDVI2005;IBI2005;NDISI2005]},... {[albedo2008;NDVI2008;IBI2008;NDISI2008]},{[albedo2010;NDVI2010;IBI2010;NDISI2010]},... {[albedo2012;NDVI2012;IBI2012;NDISI2012]},{[albedo2014;NDVI2014;IBI2014;NDISI2014]}]; outputs = {values_NLST85,values_NLST90,values_NLST94,values_NLST2000,values_NLST2002,values_NLST2005... ,values_NLST2008,values_NLST2010,values_NLST2012,values_NLST2014}; I could train it,but I think I can't predict with this style. please help me, thanks

Sign in to comment.

More Answers (0)

Categories

Find more on Sequence and Numeric Feature Data Workflows in Help Center and File Exchange

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!