Gene Expression Programming Algorithm for Transient Security Classification

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

@InProceedings{Abdelaziz:2012:SEMCCO,
  author =       "Almoataz Y. Abdelaziz and S. F. Mekhamer and 
                 H. M. Khattab and M. L. A. Badr and Bijaya Ketan Panigrahi",
  title =        "Gene Expression Programming Algorithm for Transient
                 Security Classification",
  booktitle =    "Proceedings of the Third International Conference on
                 Swarm, Evolutionary, and Memetic Computing, SEMCCO
                 2012",
  year =         "2012",
  editor =       "Bijaya Ketan Panigrahi and Swagatam Das and 
                 Ponnuthurai Nagaratnam Suganthan and 
                 Pradipta Kumar Nanda",
  volume =       "7677",
  series =       "Lecture Notes in Computer Science",
  pages =        "406--416",
  address =      "Bhubaneswar, India",
  month =        dec # " 20-22",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, gene
                 expression programming",
  isbn13 =       "978-3-642-35379-6",
  DOI =          "doi:10.1007/978-3-642-35380-2_48",
  bibsource =    "OAI-PMH server at works.bepress.com",
  oai =          "oai:works.bepress.com:almoataz_abdelaziz-1083",
  URL =          "http://works.bepress.com/almoataz_abdelaziz/42",
  size =         "11 pages",
  abstract =     "In this paper, a gene expression programming (GEP)
                 based algorithm is implemented for power system
                 transient security classification. The GEP algorithms
                 as evolutionary algorithms for pattern classification
                 have recently received attention for classification
                 problems because they can perform global searches. The
                 proposed methodology applies the GEP for the first time
                 in transient security assessment and classification
                 problems of power systems. The proposed algorithm is
                 examined using different IEEE standard test systems.
                 Power system three phase short circuit contingency has
                 been used to test the proposed algorithm. The algorithm
                 checks the static security status of the power system
                 then classifies the transient security of the power
                 system as secure or not secure. Performance of the
                 algorithm is compared with other neural network based
                 classification algorithms to show its superiority for
                 transient security classification.",
}

Genetic Programming entries for Almoataz Y Abdelaziz Said Fouad Mohamed Mekhiemar H M Khattab Mohamed Abd Ellatif Ahmed Badr Bijaya Ketan Panigrahi

Citations