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Categoria WoS
  • Artificial Neural Networks
  • Genetic Algorithms
Titulo: Diversity and Multimodal Search with a Hybrid Two-Population GA: An Application to ANN Development
Tipo: revista internacional
Fecha: 6,2005
Revista: Lecture Notes in Computer Science. Computacional Intelligence and Bioinspired System
JCR Journal; Impact Factor: 0.513
Citas Google Scholar: 2
Volumen: LNCS 3512
Paginas: 382-390
ISSN: 0302-9743
Editorial: Springer-Verlag
Berlin (Alemania)
doi: 10.1007/11494669_47


Being based on the theory of evolution and natural selection, the Genetic Algorithms (GA) represent a technique that has been proved as good enough for the resolution of those problems that require a search through a complex space of possible solutions. The maintenance of a population of possible solutions that are in constant evolution may lead to its diversity being lost, consequently it would be more difficult, not only the achievement of a final solution but also the supply of more than one solution The method that is described here tries to overcome those difficulties by means of a modification in traditional GA?s. Such modification involves the inclusion of an additional population that might avoid the mentioned loss of diversity of classical GA?s. This new population would also provide the piece of exhaustive search that allows to provide more than one solution.

    .: SABIA :.  Sistemas Adaptativos y Bioinspirados en Inteligencia Artificial