Multi-Gene Genetic Programming for Short Term Load Forecasting

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

  author =       "W. T. Ghareeb and E. F. {El Saadany}",
  booktitle =    "3rd International Conference on Electric Power and
                 Energy Conversion Systems (EPECS 2013)",
  title =        "Multi-Gene Genetic Programming for Short Term Load
  year =         "2013",
  month =        "2-4 " # oct,
  keywords =     "genetic algorithms, genetic programming, Short-term
                 load forecasting, multi-gene genetic programming,
                 radial basis function",
  DOI =          "doi:10.1109/EPECS.2013.6713061",
  abstract =     "The Short Term Load Forecasting (STLF) plays a
                 critical role in power system operation. The accuracy
                 of the STLF is very important since it affects the
                 generation scheduling and the electricity prices and
                 hence an accurate STLF method should be used. This
                 paper presents a new variant of genetic programming
                 namely: Multi-Gene Genetic Programming (MGGP) for the
                 problem of STLF. In order to demonstrate this technique
                 capability, the MGGP has been compared with the RBF
                 network and the standard single-gene Genetic
                 Programming (GP) in terms of the forecasting accuracy.
                 The data used in this study is a real data set of the
                 Egyptian electrical network. The weather factors
                 represented by the minimum and the maximum daily
                 temperature have been included in this study. The MGGP
                 has successfully predicted the future load with high
                 accuracy compared to that of the Radial Basis Function
                 (RBF) network and that of the standard single-gene
                 Genetic Programming (GP).",
  notes =        "Also known as \cite{6713061}",

Genetic Programming entries for Wael Taha Ghareeb Ehab El-Saadany