A Hybrid Genetic Programming with Particle Swarm Optimization

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@InProceedings{conf/swarm/QiMLJ13,
  author =       "Feng Qi and Yinghong Ma and Xiyu Liu and 
                 Guangyong Ji",
  title =        "A Hybrid Genetic Programming with Particle Swarm
                 Optimization",
  booktitle =    "Proceedings 4th International Conference on Advances
                 in Swarm Intelligence, ICSI 2013, Part {II}",
  year =         "2013",
  editor =       "Ying Tan and Yuhui Shi and Hongwei Mo",
  volume =       "7929",
  series =       "Lecture Notes in Computer Science",
  pages =        "11--18",
  address =      "Harbin, China",
  month =        jun # " 12-15",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, PSO",
  isbn13 =       "978-3-642-38714-2",
  URL =          "http://dx.doi.org/10.1007/978-3-642-38715-9",
  DOI =          "doi:10.1007/978-3-642-38715-9_2",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/conf/swarm/icsi2013-2.html#QiMLJ13",
  size =         "8 pages",
  abstract =     "By changing the linear encoding and redefining the
                 evolving rules, particle swarm algorithm is introduced
                 into genetic programming and an hybrid genetic
                 programming with particle swarm optimisation (HGPPSO)
                 is proposed. The performance of the proposed algorithm
                 is tested on tow symbolic regression problem in genetic
                 programming and the simulation results show that HGPPSO
                 is better than genetic programming in both convergence
                 times and average convergence generations and is a
                 promising hybrid genetic programming algorithm.",
}

Genetic Programming entries for Feng Qi Yinghong Ma Xiyu Liu Guangyong Ji

Citations