Hello everyone,
I have a dataset with corn yiel on county level in USA, with meteo data and vegetation indices, i tried several machine learning algorithms for the yield prediction, the best one was SVR that yields to 77% of accuracy. i want to try a deep learning algorithm with hope that can give better results.
Can u suggest to me some deep learning algorithm to try ?
Thank you in advance.
Sir, you are doing Very good reasearch on corn related with
metrological database it's gives you perfect prediction on good yield I think you used latest technologies for deep root study agar based also one probe inserted in stem and all data collected requirements of water nutrition show on concern scientists predicted requirements on computer screen.so you use that's instrument.I will send you details in few days my contact number is 9424295590.
This seems like a time series related prediction problem you are trying to solve.
Therefor I suspect you can get better results using not only regression based algorithms, but ones that consider the order (the time component) of the input data. Try LSTM (Long-Short Term Memory) prediction.
Good Luck
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