A stepwise model to predict monthly streamflow

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Anas Mahmood Al-Juboori and Aytac Guven",
  title =        "A stepwise model to predict monthly streamflow",
  journal =      "Journal of Hydrology",
  volume =       "543, Part B",
  pages =        "283--292",
  year =         "2016",
  ISSN =         "0022-1694",
  DOI =          "doi:10.1016/j.jhydrol.2016.10.006",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0022169416306382",
  abstract =     "In this study, a stepwise model empowered with genetic
                 programming is developed to predict the monthly flows
                 of Hurman River in Turkey and Diyalah and Lesser Zab
                 Rivers in Iraq. The model divides the monthly flow data
                 to twelve intervals representing the number of months
                 in a year. The flow of a month, t is considered as a
                 function of the antecedent month's flow (t - 1) and it
                 is predicted by multiplying the antecedent monthly flow
                 by a constant value called K. The optimum value of K is
                 obtained by a stepwise procedure which employs Gene
                 Expression Programming (GEP) and Nonlinear Generalized
                 Reduced Gradient Optimization (NGRGO) as alternative to
                 traditional nonlinear regression technique. The degree
                 of determination and root mean squared error are used
                 to evaluate the performance of the proposed models. The
                 results of the proposed model are compared with the
                 conventional Markovian and Auto Regressive Integrated
                 Moving Average (ARIMA) models based on observed monthly
                 flow data. The comparison results based on five
                 different statistic measures show that the proposed
                 stepwise model performed better than Markovian model
                 and ARIMA model. The R2 values of the proposed model
                 range between 0.81 and 0.92 for the three rivers in
                 this study.",
  keywords =     "genetic algorithms, genetic programming, Monthly
                 streamflow, Gene Expression Programming, Generalized
                 Reduced Gradient Optimization, Markovian model, ARIMA",

Genetic Programming entries for Anas Mahmood Al-Juboori Aytac Guven