Genetic Programming Applied to Predictive Control in Environmental Engineering

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

@InProceedings{Flas09a,
  author =       "Oliver Flasch and Thomas Bartz-Beielstein and 
                 Patrick Koch and Wolfgang Konen",
  title =        "Genetic Programming Applied to Predictive Control in
                 Environmental Engineering",
  booktitle =    "Proceedings 19. Workshop Computational Intelligence",
  year =         "2009",
  editor =       "Frank Hoffmann and Eyke Huellermeier",
  pages =        "101--113",
  publisher =    "KIT Scientific Publishing",
  address =      "Karlsruhe",
  keywords =     "genetic algorithms, genetic programming",
  pubstate =     "published",
  annote =       "Fakult{\"a}t F{\"u}r Informatik Und
                 Ingenieurwissenschaften; The Pennsylvania State
                 University CiteSeerX Archives",
  bibsource =    "OAI-PMH server at citeseerx.ist.psu.edu",
  language =     "en",
  oai =          "oai:CiteSeerX.psu:10.1.1.301.5641",
  rights =       "Metadata may be used without restrictions as long as
                 the oai identifier remains attached to it.",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.301.5641",
  URL =          "http://lwibs01.gm.fh-koeln.de/blogs/konen/publications-wolfgang-konen/?tgid=20&yr&type&auth",
  URL =          "http://www.gm.fh-koeln.de/~bartz/Papers.d/Flas09a.pdf",
  abstract =     "We introduce a new hybrid Genetic Programming (GP)
                 based method for time series prediction in predictive
                 control applications. Our method combines existing
                 state-of-the-art analytical models from predictive
                 control with a modern typed graph GP system. The main
                 idea is to pre-structure the GP search space with
                 existing analytical models to improve prediction
                 accuracy. We apply our method to a difficult predictive
                 control problem from the water resource management
                 industry, yielding an improved prediction accuracy,
                 compared with both the best analytical model and with a
                 modern GP method for time series prediction. Even if we
                 focus this first study on predictive control, the
                 automatic optimisation of existing models through GP
                 shows a great potential for broader application.",
}

Genetic Programming entries for Oliver Flasch Thomas Bartz-Beielstein Patrick Koch Wolfgang Konen

Citations