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1	Genetinių algoritmų pritaikymo klasifikavimo uždaviniams spręsti tyrimas / Genetic Algorithms in Classification tasks solving Balnys, Mantas 28 May 2004 (has links) 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. Informatics Evoliutionary Computation Neural Networks Genetic Algorithms Neuroninių tinklų apmokymas Parameter less Genetic Algorithm Classification tasks Neuroniniai tinklai Evoliuciniai skaičiavimai Beparametrinis genetinis algoritmas Klasifikavimo uždaviniai Genetiniai algoritmai Teaching