Selecting the appropriate data that fulfils most of the system's dynamics needs to be carefully done. We want the neural network to forecast future weather based on the current and past weather data, but which variables should we choose? Getting an expert opinion on the subject can be really helpful in understanding the relationship between variables.
Tip
Regarding time series variables, one can derive new variables by applying historical data. That means, given a certain date, one may consider this date's values and the data collected (and/or summarized) from past dates, therefore extending the number of variables.
While defining a problem to use neural networks on, there are one or more predefined target variables: predict the temperature, forecast precipitation. measure insolation, and so on. But, in some cases, one wants to model all the variables and therefore to find causal relationships between them. Causal relationships can be identified by statistical...