How to feed two (or more) time-series data sets to a neural network? I want to train the network based on two sets of data. For example, I want the network to predict the humidity based on past humidity trends AND past temperature trends. In this case, how should I organize the input layer? I would think that for just one time-series, I would use a regular sliding window on the series. With two series, do I just present both windows (from the humidity and temperature series) to the input layer that is twice the size of the window? if not, how else can I configure the input layer so that it doesn't confuse between the two sets of training data?﻿

Do I just let the network sort this out by itself or is there a preferred method of presenting two (or more) sets of training data to the network? Thanks.
The whole idea of NN is that it learns by itself to give the appropriate weights and biases to the input neurons, so yes - just give your network the 2 series and it should return the appropriate weight and bias for each neuron in the input.