Learning Time Series Patterns by Genetic Programming

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

@InProceedings{conf/acsc/XieSC12,
  author =       "Feng Xie and Andy Song and Victor Ciesielski",
  title =        "Learning Time Series Patterns by Genetic Programming",
  booktitle =    "Thirty-Fifth Australasian Computer Science Conference,
                 ACSC 2012",
  year =         "2012",
  editor =       "Mark Reynolds and Bruce H. Thomas",
  volume =       "122",
  series =       "CRPIT",
  pages =        "57--62",
  address =      "Melbourne, Australia",
  month =        jan,
  publisher =    "Australian Computer Society",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-1-921770-03-6",
  URL =          "http://crpit.com/Vol122.html",
  URL =          "http://crpit.com/confpapers/CRPITV122Xie.pdf",
  bibdate =      "2013-04-21",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/conf/acsc/acsc2012.html#XieSC12",
  size =         "6 pages",
  abstract =     "Finding patterns such as increasing or decreasing
                 trends, abrupt changes and periodically repeating
                 sequences is a necessary task in many real world
                 situations. We have shown how genetic programming can
                 be used to detect increasingly complex patterns in time
                 series data. Most classification methods require a
                 hand-crafted feature extraction preprocessing step to
                 accurately perform such tasks. In contrast, the evolved
                 programs operate on the raw time series data. On the
                 more difficult problems the evolved classifiers
                 outperform the OneR, J48, Naive Bayes, IB1 and Adaboost
                 classifiers by a large margin. Furthermore this method
                 can handle noisy data. Our results suggest that the
                 genetic programming approach could be used for
                 detecting a wide range of patterns in time series data
                 without extra processing or feature extraction.",
  notes =        "ACSC",
}

Genetic Programming entries for Feng Xie Andy Song Victor Ciesielski

Citations