A New Methodology For Deriving Regional Time Of Concentration Equations Using GIS And Genetic Programming

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

@InProceedings{Sharifi:2014:HIC,
  author =       "Soroosh Sharifi and Mahdi Razaz",
  title =        "A New Methodology For Deriving Regional Time Of
                 Concentration Equations Using GIS And Genetic
                 Programming",
  booktitle =    "11th International Conference on Hydroinformatics",
  year =         "2014",
  pages =        "Paper 307",
  address =      "New York, USA",
  month =        aug # " 17-21",
  organisation = "IAHR/IWA Joint Committee on Hydroinformatics",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-0-692-28129-1",
  URL =          "http://academicworks.cuny.edu/cc_conf_hic/307/",
  URL =          "http://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1306&context=cc_conf_hic.pdf",
  broken =       "http://www.hic2014.org/proceedings/bitstream/handle/123456789/1531/1556.pdf",
  size =         "8 pages",
  abstract =     "In this study, a methodology is proposed for deriving
                 Time of concentration (ToC) equations for watersheds
                 located in a specific geographic region using GIS and
                 Genetic Programming (GP). In this method, true ToC
                 values are calculated by integrating GIS data into the
                 TR-55 model and using the travel time method. GP is
                 then used as a data-mining tool for conducting symbolic
                 regression and deriving the most accurate equations for
                 the region's watersheds. In a case study, the proposed
                 methodology is applied to 72 watersheds and
                 sub-watersheds in Khorasan Razavi province, Iran. The
                 method provides a set of different ToC equations to be
                 used for watersheds in the region. Performance
                 evaluation of the equations mined by GP shows that this
                 approach is able to find ToC equations that are more
                 accurate and robust compared to conventional ToC
                 equations. Also, the derived equations shed some light
                 on the important parameters that influence the ToC of a
                 watershed.",
  notes =        "http://www.hic2014.org/xmlui/",
}

Genetic Programming entries for Soroosh Sharifi Mahdi Razaz

Citations