Ensemble of genetic programming models for designing reactive power controllers

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

@InProceedings{grosan:2005:HIS,
  author =       "C. Grosan and A. Abraham",
  title =        "Ensemble of genetic programming models for designing
                 reactive power controllers",
  booktitle =    "Fifth International Conference on Hybrid Intelligent
                 Systems, HIS-05",
  year =         "2005",
  month =        "6-9 " # nov,
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/ICHIS.2005.36",
  abstract =     "In this paper, we present an ensemble combination of
                 two genetic programming models namely linear genetic
                 programming (LGP) and multi expression programming
                 (MEP). The proposed model is designed to assist the
                 conventional power control systems with added
                 intelligence. For on-line control, voltage and current
                 are fed into the network after preprocessing and
                 standardisation. The model was trained with a 24-hour
                 load demand pattern and performance of the proposed
                 method is evaluated by comparing the test results with
                 the actual expected values. For performance comparison
                 purposes, we also used an artificial neural network
                 trained by a backpropagation algorithm. Test results
                 reveal that the proposed ensemble method performed
                 better than the individual GP approaches and artificial
                 neural network in terms of accuracy and computational
                 requirements.",
}

Genetic Programming entries for Crina Grosan Ajith Abraham

Citations