Forecasting short-term electricity consumption using a semantics-based genetic programming framework: The South Italy case

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Castelli:2015:EE,
  author =       "Mauro Castelli and Leonardo Vanneschi and 
                 Matteo {De Felice}",
  title =        "Forecasting short-term electricity consumption using a
                 semantics-based genetic programming framework: The
                 South Italy case",
  journal =      "Energy Economics",
  volume =       "47",
  pages =        "37--41",
  year =         "2015",
  ISSN =         "0140-9883",
  DOI =          "doi:10.1016/j.eneco.2014.10.009",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0140988314002539",
  abstract =     "Accurate and robust short-term load forecasting plays
                 a significant role in electric power operations. This
                 paper proposes a variant of genetic programming,
                 improved by incorporating semantic awareness in
                 algorithm, to address a short term load forecasting
                 problem. The objective is to automatically generate
                 models that could effectively and reliably predict
                 energy consumption. The presented results, obtained
                 considering a particularly interesting case of the
                 South Italy area, show that the proposed approach
                 outperforms state of the art methods. Hence, the
                 proposed approach reveals appropriate for the problem
                 of forecasting electricity consumption. This study,
                 besides providing an important contribution to the
                 energy load forecasting, confirms the suitability of
                 genetic programming improved with semantic methods in
                 addressing complex real-life applications.",
  keywords =     "genetic algorithms, genetic programming, Forecasting,
                 Electricity demand, Semantics",
}

Genetic Programming entries for Mauro Castelli Leonardo Vanneschi Matteo De Felice

Citations