Alternative well calibrated rainfall-runoff model: Genetic programming scheme

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@InProceedings{Liong2001777,
  author =       "Shie-Yui Liong and V. T. Van Nguyen and 
                 Tirtha Raj Gautam and Loong Wee",
  title =        "Alternative well calibrated rainfall-runoff model:
                 Genetic programming scheme",
  booktitle =    "Urban Drainage Modeling",
  year =         "2001",
  editor =       "R W Brashear and C Maksimovic and R W Brashear and 
                 C Maksimovic",
  pages =        "777--787",
  address =      "Orlando, Florida, USA",
  month =        may # " 20-24",
  publisher =    "American Society of Civil Engineers",
  keywords =     "genetic algorithms, genetic programming, Catchments,
                 Computer simulation, Mathematical models, Optimisation,
                 Runoff, Storms, Weather forecasting, Rainfall runoff
                 model, Storm water management model, Rain gauges",
  isbn13 =       "978-0-7844-0583-3",
  URL =          "http://ascelibrary.org/doi/abs/10.1061/40583%28275%2973",
  DOI =          "doi:10.1061/40583(275)73",
  size =         "11 pages",
  abstract =     "Genetic Programming (GP) has been explored as a flow
                 forecasting tool. A catchment in Singapore with a
                 drainage area of about 6 km2 is used for this case
                 study. GP was trained to simulate runoff from a
                 conceptual rainfall-runoff model, Storm Water
                 Management Model (SWMM), which was first calibrated
                 using Shuffled Complex Evolution (SCE) algorithm. Four
                 storms of different intensities and durations are used
                 for training and verification of the GP models. The
                 results show that the runoff prediction accuracy of
                 genetic programming based tool, measured in terms of
                 root mean square error and correlation coefficient, is
                 reasonably high. Thus, GP coupled with a robust
                 optimisation scheme such as SCE is a viable
                 complementary tool to traditional conceptual
                 rainfall-runoff models.",
  notes =        "GPKernel Babovic",
  affiliation =  "Department of Civil Engineering, National University
                 of Singapore, 10 Kent Ridge Crescent, Singapore 119260,
                 Singapore",
  correspondence_address1 = "Liong, S.-Y.; Department of Civil
                 Engineering, National University of Singapore, 10 Kent
                 Ridge Crescent, Singapore 119260, Singapore; email:
                 cvelsy@nus.edu.sg",
  language =     "English",
  document_type = "Conference Paper",
}

Genetic Programming entries for Shie-Yui Liong Van-Thanh-Van Nguyen Tirtha Raj Gautam Loong Wee

Citations