So you're trying to optimise a neural network using genetic algorithm, right? Cool!
It is usually advised to use normalised input to ANN, but this is particularly applicable when using sigmoid activation. Are you sure you need normalised data? Without knowing the range of your input, it is quite difficult to get the ANN to do its job.
- If you're hard pressed on normalising the input, keep track of the current maxima and minima in your data.
- Better still, try to iterate over the data once to gather apriori information about maxima and minima (only if it doesn't significantly add to the time complexity).
- Or else, try investigating a logic to guess the maxima and minima. Maybe... another neural network to do the guess work :). This will depend upon the environment.
What you're trying to do is not very clear to me... but from what I understand, these are the only suggestions I could come up with.
Check these two links. Might help: