LSTM Feature selection process
Have you tried to do a correlation test between the output and the features used to model it?

I usually use Pearson's Correlation to determine the features with low correlation factors. Then I remove them from the training.

In here, I have DOC_DS used to model DOC_US, I have them both in a data frame df with my other features. From the trails I did on my models, the features with less correlation affects the model accuracy later on.

In Python Environment:

print(np.array_str(np.corrcoef(df.DOC_DS,df.DOC_US)))