Created by W.Langdon from gp-bibliography.bib Revision:1.5251
Instead of a human developing the mechanistic-based model, this paper presents an approach to automatic model evolution in genetic programming (GP) to model dynamic behaviour of groundwater level fluctuations affected by storm water infiltration. This GP evolves mathematical models automatically that have an understandable structure using function tree representation by methods of natural selection ('survival of the fittest') through genetic operators (reproduction, crossover, and mutation).
The simulation results have shown that GP is not only capable of predicting the groundwater level fluctuation due to storm water infiltration but also provides insight into the dynamic behaviour of a partially known urban fractured-rock aquifer system by allowing knowledge extraction of the evolved models. Our results show that GP can work as a cost-effective modelling tool, enabling us to create prototype models quickly and inexpensively and assists us in developing accurate models in less time, even if we have limited experience and incomplete knowledge for an urban fractured-rock aquifer system affected by storm water infiltration.",
Genetic Programming entries for Yoon-Seok Hong Michael R Rosen