Month Ahead Rainfall Forecasting Using Gene Expression Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4504

  author =       "Ali {Danandeh Mehr}",
  title =        "Month Ahead Rainfall Forecasting Using Gene Expression
  journal =      "American Journal of Earth and Environmental Sciences",
  year =         "2018",
  volume =       "1",
  number =       "2",
  pages =        "63--70",
  month =        "10 " # apr,
  keywords =     "genetic algorithms, genetic programming, Gene
                 Expression Programming, Monthly Rainfall, Time Series
                 Modelling, State-Space Modelling",
  URL =          "",
  size =         "8 pages",
  abstract =     "In the present study, gene expression programming
                 (GEP) technique was used to develop one-month ahead
                 monthly rainfall forecasting models in two
                 meteorological stations located at a semi-arid region,
                 Iran. GEP was trained and tested using total monthly
                 rainfall (TMR) time series measured at the stations.
                 Time lagged series of TMR samples having weak
                 stationary state were used as inputs for the modelling.
                 Performance of the best evolved models were compared
                 with those of classic genetic programming (GP) and
                 autoregressive state-space (ASS) approaches using
                 coefficient of efficiency (R2) and root mean squared
                 error measures. The results showed good performance
                 (0.532 less than 0.56) for GEP models at testing
                 period. In both stations, the best model evolved by GEP
                 outperforms the GP and are significantly superior to
                 the ASS models.",
  notes =        "Civil Engineering Department, Antalya Bilim
                 University, Antalya,


Genetic Programming entries for Ali Danandeh Mehr