问题
I am using Neural Network technique(Backward Learning). As a output for example I am giving the 18 point ahead value and as input I gave the latest 5 point to train.(I tried the many combinations of input data 5,10, 20 ,30...).
For example, the way I trained my data:
t, t+1, t+2, t+3, t+4... => t+22(4+18)
t+1, t+2, t+3, t+4, t+5... => t+23
Exponential inputs:
t, t+1, t+2, t+4, t+8... => t+26(8+18)
t+1, t+2, t+3, t+8, t+9... => t+27
After I trained, I have done forward learning with the my trained values. I have observed that neural network won't able to catch the sudden peaks. Most of the time if I am going to predict 18 seconds ahead, it predicts the correct result 17 seconds later.
Do you have any advice for me about how could I able to predict sudden peaks(that will happen t seconds later) with neural network?
回答1:
I work with backpropagation and I observe the same behaviour. If I understood correctly, you don't have a true forecasting. Peeks, when present on data, are available to be "predicted" only after appear in the series, and you observe and apparent prediction with a delay.
I thinf you have to user a recurrent network.
来源：https://stackoverflow.com/questions/20359362/early-detection-of-peaks-with-neural-network