Time Series Prediction Using Grammar-directed Genetic Programming Methods

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  author =       "Santi {Garcia Carbajal}",
  title =        "Time Series Prediction Using Grammar-directed Genetic
                 Programming Methods",
  howpublished = "NN3 Artificial Neural Network \& Computational
                 Intelligence 2006/07 Forecasting Competition for Neural
                 Networks \& Computational Intelligence",
  year =         "2007",
  note =         "ISF-2007, IJCNN 2007, DMIN 2007",
  keywords =     "genetic algorithms, genetic programming",
  bibsource =    "OAI-PMH server at citeseerx.ist.psu.edu",
  language =     "en",
  oai =          "oai:CiteSeerX.psu:",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=",
  URL =          "http://www.neural-forecasting-competition.com/downloads/NN3/methods/55-NN3-Carjabal.pdf",
  URL =          "http://www.neural-forecasting-competition.com/NN3/results.htm",
  size =         "4 pages",
  abstract =     "We use a modified Genetic Programming System to
                 predict the values of the reduced set proposed as
                 benchmark for the 2007 Neural Forecasting Contest.
                 Genetic Programming is a well known method used in
                 symbolic regression, and classification, based in the
                 evolution of arithmetic expressions according to a
                 fitness function. We introduce here a grammar into the
                 Genetic system, to let us use conditional expressions
                 inside the syntactic trees representing the solutions
                 to the problem. Additionally, we employ GA-P methods to
                 automatically obtain constants inside the expressions.
                 Our results proof the known power of Genetic
                 Programming as a tool for solving Symbolic Regression
                 problems, as the obtained expressions fit acceptably
                 the proposed series. For the predicted values, some of
                 them seem promising while others present too flat

Genetic Programming entries for Santiago Garcia Carbajal