Emergent system identification using particle swarm optimization

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

@InProceedings{2001SPIE.4512..193V,
  author =       "Mark S. Voss and Xin Feng",
  title =        "Emergent system identification using particle swarm
                 optimization",
  booktitle =    "Procceedings of SPIE: Complex Adaptive Structures",
  year =         "2001",
  month =        oct,
  adsurl =       "http://adsabs.harvard.edu/cgi-bin/nph-bib_query?bibcode=2001SPIE.4512..193V&db_key=AST",
  adsnote =      "Provided by the NASA Astrophysics Data System",
  editor =       "William B. Spillman",
  volume =       "4512",
  pages =        "193--202",
  organisation = "SPIE--The International Society for Optical
                 Engineering",
  keywords =     "genetic algorithms, genetic programming, PSO, GMDH",
  URL =          "http://www.evolutionarystructures.com/papers/88338032.pdf",
  URL =          "http://adsabs.harvard.edu/cgi-bin/nph-bib_query?2001SPIE.4512..193V",
  URL =          "http://citeseer.ist.psu.edu/560788.html",
  DOI =          "doi:10.1117/12.446767",
  size =         "10 pages",
  abstract =     "Complex Adaptive Structures can be viewed as a
                 combination of Complex Adaptive Systems and fully
                 integrated autonomous Smart Structures. Traditionally
                 when designing a structure, one combines rules of thumb
                 with theoretical results to develop an acceptable
                 solution. This methodology will have to be extended for
                 Complex Adaptive Structures, since they, by definition,
                 will participate in their own design. In this paper we
                 introduce a new methodology for Emergent System
                 Identification that is concerned with combining the
                 methodologies of self-organising functional networks
                 (GMDH - Alexy G. Ivakhnenko), Particle Swarm
                 Optimization (PSO - James Kennedy and Russell C.
                 Eberhart) and Genetic Programming (GP - John Koza).
                 This paper will concentrate on the use of Particle
                 Swarm Optimisation in this effort and discuss how
                 Particle Swarm Optimization relates to our ultimate
                 goal of emergent self-organizing functional networks
                 that can be used to identify overlapping internal
                 structural models. The ability for Complex Adaptive
                 Structures to identify emerging internal models will be
                 a key component for their success.",
}

Genetic Programming entries for Mark S Voss Xin Feng

Citations