For some Time Series Prediction problems it is important to evolve a model that performs well for all fitness cases within a certain absolute error (the
precision) of the correct value.
For those cases, the fitness f(ij) of an individual program
i for fitness case j is evaluated by the formula:

where p is the precision and E(ij) is the absolute error of an individual program
i for fitness case j evaluated by the equation: 
where P(ij) is the value predicted by the individual program
i for fitness case j and Tj is the target value for fitness case
j.
So, for this fitness function, maximum fitness fmax is given by: fmax =
n
where n is the number of fitness cases.
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