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Symbolic regression (SR) is an attractive modeling approach because it can capture and present, mathematically, relationships between variables of interest. However, given n variables to model, symbolic regression returns a flat list of n equations. As the number of state variables to be modeled scales, interpretation of such a list becomes difficult. Here we present a symbolic regression method that...
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