A Review on Application of Soft Computing Methods in Water Resources Engineering

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

@InCollection{Azamathulla:2013:MWGTE,
  author =       "H. Md Azamathulla",
  title =        "A Review on Application of Soft Computing Methods in
                 Water Resources Engineering",
  booktitle =    "Metaheuristics in Water, Geotechnical and Transport
                 Engineering",
  publisher =    "Elsevier",
  address =      "Oxford",
  year =         "2013",
  chapter =      "2",
  pages =        "27--41",
  keywords =     "genetic algorithms, genetic programming, gene
                 expression programming, Water resources engineering,
                 applied soft computing, artificial neural network,
                 adaptive neuro-fuzzy inference system, scour, river
                 stage",
  isbn13 =       "978-0-12-398296-4",
  DOI =          "doi:10.1016/B978-0-12-398296-4.00002-7",
  URL =          "http://www.sciencedirect.com/science/article/pii/B9780123982964000027",
  abstract =     "This chapter reviews the application of soft computing
                 techniques, namely radial basis function (RBF),
                 adaptive neuro-fuzzy inference system (ANFIS),
                 gene-expression programming (GEP), and linear genetic
                 programming (LGP) in water resources engineering. The
                 capabilities of these techniques have been illustated
                 by applying them to the prediction of scour downstream
                 of flip spillway/bridge pier and abutment
                 scour/pipeline scour/culvert scour/sediment load in
                 hydraulics, and the river stage-discharge curve in
                 hydrology. The accuracy of the results obtained by the
                 soft computing techniques supports their further use
                 for the prediction of hydraulic and hydrologic
                 variables. Availability of free and easy-to-apply
                 software for a specified method can invite a huge
                 number of its applications by enthusiastic
                 investigators.",
}

Genetic Programming entries for Hazi Mohammad Azamathulla

Citations