# Time Series Forecasting - Recurrent Neural Networks (tensorflow)

I am attempting to forecast a time series using tensorflow with the following code:

X = mytimeseries
scaler = MinMaxScaler()
scaled = scaler.fit_transform(X)

length = len(X)-1
generator = TimeseriesGenerator(scaled,scaled,
length=length,batch_size=1)

model = Sequential()

I have tried increasing the number of neurons in the dense layer, units in the LSTM cell, etc. At the moment, the thing that looks like to most effect the resultant curve is to change the length parameter in my code above. But all this does is make the predictions more sinusoidal.