Original title: Genetic Selection and Cloning in GMDH MIA Method
Translated title: Genetická selekce a klonování u metody GMDH-MIA
Authors: Jiřina, Marcel ; Jiřina jr., M.
Document type: Papers
Conference/Event: IWIM 2007, Prague (CZ), 2007-09-22 / 2007-09-26
Year: 2007
Language: eng
Abstract: [eng] [cze]
The GMDH MIA algorithm is modified by the use of selection procedure from genetic algorithms and including cloning of the best neurons generated. The selection procedure finds parents for a new neuron among already existing neurons according to fitness and with some probability also from network inputs. The essence of cloning is slight modification of parameters of copies of the best neuron, i.e. neuron with the largest fitness. The genetically modified GMDH network with cloning (GMC-GMDH) can outperform other powerful methods. It is demonstrated on some tasks from Machine Learning Repository. Algoritmus GMDH-MIA byl modifikován použitím selekční procedury z genetických algoritmů a zahrnutím klonování. Selekční procedura najde rodiče pro nový neuron mezi již existujícími neurony podle jejich fitness a s určitou pravděpodobností také mezi vstupy sítě. Podstatou klonování je malá modifikace parametrů nejlepšího neuronu. Geneticky modifikovaná síť GMDH s kolonováním (GMC-GMDH) je schopna lepších výsledků než jiné výkonné metody. Je to ukázáno na některých datech z Machine Learning Repository.
Keywords: artificial neural networks; cloning; genetic algorithm; genetic selection; GMDH MIA algorithm; inductive modeling
Project no.: CEZ:AV0Z10300504 (CEP), 1M0567 (CEP)
Funding provider: GA MŠk
Host item entry: International Workshop on Inductive Modelling, ISBN 978-80-01-03881-9

Institution: Institute of Computer Science AS ČR (web)
Document availability information: Fulltext is available in the digital repository of the Academy of Sciences.
Original record: http://hdl.handle.net/11104/0148821

Permalink: http://www.nusl.cz/ntk/nusl-37456


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Research > Institutes ASCR > Institute of Computer Science
Conference materials > Papers