Ground Resistance Estimation using Genetic Programming

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

  author =       "Konstantinos Boulas and Valilios P. Androvitsaneas and 
                 Ioannis F. Gonos and Georgios Dounias and 
                 Ioannis A. Stathopulos",
  title =        "Ground {Resistance} {Estimation} using {Genetic}
  booktitle =    "5th International Symposium and 27th National
                 Conference on Operation Research",
  editor =       "Athanasios Spyridakos and Lazaros Vryzidis",
  year =         "2016",
  month =        jun,
  address =      "Aigaleo, Athens",
  pages =        "66--71",
  keywords =     "genetic algorithms, genetic programming, gene
                 expression programming, symbolic regression, ground
  isbn13 =       "978-618-80361-6-1",
  URL =          "",
  abstract =     "The objective of this paper is to use genetic
                 programming methodologies for the modelling and
                 estimation of ground resistance with the use of field
                 measurements related to weather data. Grounding is
                 important for the safe operation of any electrical
                 installation and protects it against lightning and
                 fault currents. The work utilizes both, conventional
                 and intelligent data analysis techniques, for ground
                 resistance modeling from field measurements.
                 Experimental data consist of field measurements that
                 have been performed in Greece during the previous four
                 years. Five linear regression models have been applied
                 to a properly selected dataset, as well as an
                 intelligent approach based on Gene Expression
                 Programming (GEP). Every model corresponds to a
                 specific grounding system. A heuristic approach using
                 GEP was performed in order to produce more robust and
                 general models for grounding estimation. The results
                 show that evolutionary techniques such as those based
                 on Genetic Programming (GP) are promising for the
                 estimation of the ground resistance.",

Genetic Programming entries for Konstantinos Boulas Valilios P Androvitsaneas Ioannis F Gonos Georgios Dounias Ioannis A Stathopulos