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Electricity consumption forecasting using LSTM RNNs 

The Simulation Guy
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Long short-term memory (LSTM) recurrent neural networks are often used for forecasting. In this video, household power consumption dataset is used to predict future power consumption. For that, LSTM based deep learning neural network is built.
github.com/thesimulationguy/H...

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26 июн 2019

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Комментарии : 7   
@haneensuradi
@haneensuradi 4 года назад
It would have been good if you showed the predicted vs actual consumption during the four years. It will be even more interesting to predict the consumption for 2011 year without having an actual data to compare with.
@krishnayogi
@krishnayogi 4 года назад
Good stuff buddy keep going
@bkameswari6216
@bkameswari6216 2 года назад
If you are explaining then it's good
@pravuchaudhary3904
@pravuchaudhary3904 3 года назад
where did you get the data?
@hemantashahi6370
@hemantashahi6370 4 года назад
Got some errors : array split does not result in equal division.can you help?
@hamidbasiri8565
@hamidbasiri8565 2 года назад
Did you solve the error?
@CartwheelPig
@CartwheelPig 4 месяца назад
Just replace the split function with this code: def split(data): print(len(data)) half = int(len(data)/2) train = data[0:half-2] test = data[half+1:len(data)-1] print(len(train), len(test)) train=np.array(np.split(train,len(train)/7)) test=np.array(np.split(test,len(test)/7)) return train,test
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