Identification of an urban fractured-rock aquifer dynamics using an evolutionary self-organizing modelling

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{Hong:2002:JH,
  author =       "Yoon-Seok Hong and Michael R. Rosen",
  title =        "Identification of an urban fractured-rock aquifer
                 dynamics using an evolutionary self-organizing
                 modelling",
  journal =      "Journal of Hydrology",
  year =         "2002",
  volume =       "259",
  pages =        "89--104",
  number =       "1-4",
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "0022-1694",
  owner =        "wlangdon",
  URL =          "http://www.sciencedirect.com/science/article/B6V6C-44KPK1K-4/2/cc33fdeeff7d3869ee62940e37e3e133",
  DOI =          "doi:10.1016/S0022-1694(01)00587-X",
  abstract =     "An urban fractured-rock aquifer system, where disposal
                 of storm water is via 'soak holes' drilled directly
                 into the top of fractured-rock basalt, has a highly
                 dynamic nature where theories or knowledge to generate
                 the model are still incomplete and insufficient.
                 Therefore, formulating an accurate mechanistic model,
                 usually based on first principles (physical and
                 chemical laws, mass balance, and diffusion and
                 transport, etc.), requires time- and money-consuming
                 tasks.

                 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

Citations