I’m new to ML and I’m currently doing a project so that I can learn more about machine learning.
So I have a bunch of x,y,z (lat, lon, depth) data for a section of a river, which was taken at 5 intervals over a 5 month period. The river bed (the accumulation of mud) has changed over this 5 month period, and I have relevant data such as the inlet and outlet velocities, and the water temperatures. However, I think only the velocities would have the highest impact on the river bed.
I would like to use this historical data and any other relevant data I have, to try and predict how the river bed would look in the next month(s).
I have already cleaned/filtered the data and imported the data into QGIS to visualize it and I can see the river bed has in fact changed on the contour plots.
Would anyone be able to give me some pointers on how I can go about this please?
I have looked into the free version of splunk but I’m unsure whether the built-in forecasting is able to deal with multivariate predictions? It looks more suited for single variables, but I could be wrong.
Please let me know if I can provide any further info, and sorry if I’ve made any errors in posting as this is my first.
Thank you in advance.