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  • This paper describes the possibilities of using genetic algorithms for network design and optimization. The described algorithm – grammatical evolution – has strong generalizing capabilities, which allow it to generate symbolic representation of mathematics models, graphs and other structures.
  • This paper describes the possibilities of using genetic algorithms for network design and optimization. The described algorithm – grammatical evolution – has strong generalizing capabilities, which allow it to generate symbolic representation of mathematics models, graphs and other structures. (en)
Title
  • Increasing of Copmputer Networks Performance via Node to Node Throughput Optimization
  • Increasing of Copmputer Networks Performance via Node to Node Throughput Optimization (en)
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  • Increasing of Copmputer Networks Performance via Node to Node Throughput Optimization
  • Increasing of Copmputer Networks Performance via Node to Node Throughput Optimization (en)
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  • RIV/63468352:_____/08:#0000048!RIV10-MSM-63468352
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  • 371848
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  • RIV/63468352:_____/08:#0000048
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  • Grammatical evolution, evolving structures, network optimization, genetic algorithms, grammar, communication lines, nodes, throughput, performanceGrammatical evolution, evolving structures, network optimization, genetic algorithms, communication lines, nodes, throughput, algorithms (en)
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  • [189E687CBEDD]
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  • Proceedings of the Sixth International Conference on Soft Computing Applied in Computer and Economic Environments
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  • Popelka, Ondřej
  • Rukovanský, Imrich
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number of pages
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  • Evropský polytechnický institut, s.r.o.
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  • 978-80-7314-134-9
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