Time Series Forecast with Anticipation Using Genetic Programming

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

@InProceedings{conf/iwann/RiveroRDP05,
  title =        "Time Series Forecast with Anticipation Using Genetic
                 Programming",
  author =       "Daniel Rivero and Juan R. Rabunal and 
                 Julian Dorado and Alejandro Pazos",
  year =         "2005",
  pages =        "968--975",
  editor =       "Joan Cabestany and Alberto Prieto and 
                 Francisco Sandoval Hern{\'a}ndez",
  publisher =    "Springer",
  series =       "Lecture Notes in Computer Science",
  volume =       "3512",
  booktitle =    "Computational Intelligence and Bioinspired Systems,
                 8th International Work-Conference on Artificial Neural
                 Networks, IWANN 2005, Proceedings",
  address =      "Vilanova i la Geltr{\'u}, Barcelona, Spain,",
  month =        jun # " 8-10",
  bibdate =      "2005-06-27",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/conf/iwann/iwann2005.html#RiveroRDP05",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-26208-3",
  DOI =          "doi:10.1007/11494669_119",
  size =         "8 pages",
  abstract =     "application of Genetic Programming (GP) for time
                 series forecast. Although this kind of application has
                 been carried out with a wide range of techniques and
                 with very good results, this paper presents a different
                 approach. In most of the experiments done in time
                 series forecasting the objective is, from a consecutive
                 set of samples or time interval, to obtain the value of
                 the sample in the next time step. The aim of this paper
                 is to study the forecasting not only on the next
                 sample, but in general several samples forward. This
                 will allow the building of more complete prediction
                 systems. With this objective, one of the most widely
                 used series for this kind of application has been used,
                 the Mackey-Glass series.",
}

Genetic Programming entries for Daniel Rivero Cebrian Juan Ramon Rabunal Dopico Julian Dorado Alejandro Pazos Sierra

Citations