Data-Fitting, Evolutionary, and Qualitative Modeling
Daniel Peter Loucks, Eelco van Beek · 2017
Clearly, all model outputs depend on model inputs. The optimization and simulation models discussed in the previous chapters are no exception. This chapter introduces some alternative modeling approaches that depend on observed data. These approaches include artificial neural networks and various evolutionary models. The chapter ends with some qualitative modeling. These data-driven models can serve as substitutes for more process-based models in applications where computational speed is critical or where the underlying relationships are poorly understood or too complex to be easily incorporated into calculus-based, linear, nonlinear, or dynamic programming models. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.