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Genetinių algoritmų pritaikymo klasifikavimo uždaviniams spręsti tyrimas / Genetic Algorithms in Classification tasks solving

Neural networks are one of the most efficient classifier methods. One of such classifying neural networks we are trying to teach in this work by using genetic algorithms. In this work we test two types of genetic algorithms. One may be called parameterized genetic algorithm. It is built on the basic ideas of genetic algorithms. The other one is called parameter less genetic algorithm. It was presented by F. G. Lobo and D. E. Goldberg. Both genetic algorithms are tested and compared to the other well known optimization methods such as Bayes and Monte Carlo search. Experiments show the relevance of use genetic algorithms in teaching classifying neural network. Also stated that parameter less genetic algorithm works more efficient than parametric genetic algorithm in general cases. Created programs will be used in future studies.

Identiferoai:union.ndltd.org:LABT_ETD/oai:elaba.lt:LT-eLABa-0001:E.02~2004~D_20040528_155652-64676
Date28 May 2004
CreatorsBalnys, Mantas
ContributorsPlėštys, Rimantas, Barauskas, Rimantas, Palubeckis, Gintaras, Pranevičius, Henrikas, Jasinevičius, Raimundas, Telksnys, Laimutis, Matickas, Jonas Kazimieras, Kanapeckas, Pranas, Mockus, Jonas, Kaunas University of Technology
PublisherLithuanian Academic Libraries Network (LABT), Kaunas University of Technology
Source SetsLithuanian ETD submission system
LanguageLithuanian
Detected LanguageEnglish
TypeMaster thesis
Formatapplication/pdf
Sourcehttp://vddb.library.lt/obj/LT-eLABa-0001:E.02~2004~D_20040528_155652-64676
RightsUnrestricted

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