"A new procedure based on layered feedforward neural networks for the microplane material model parameters identification is proposed in the present paper. It is based on the inverse mode of inverse analysis presented in the Part I. Novelties are usage of the Latin Hypercube Sampling method for the generation of training sets, a sensitivity analysis and a genetic algorithm-based training of a neural network by an evolutionary algorithm. Advantages and disadvantages of this approach together with possible extensions are thoroughly discussed and analyzed." . . . "449516" . . "Sequential Identification of Microplane Model Parameters" . "[A95CF948DE7B]" . . "Computational and Experimental Analysis of Structure and Properties of New Building Materials from Nano- to Macrolevel IV" . "RIV/68407700:21110/07:01136215" . . . . "Postupn\u00E1 identifikace parametr\u016F mikroplo\u0161kov\u00E9ho modelu"@cs . . "Praha" . "\u010Cesk\u00E9 vysok\u00E9 u\u010Den\u00ED technick\u00E9 v Praze. Fakulta stavebn\u00ED" . . "RIV/68407700:21110/07:01136215!RIV08-MSM-21110___" . "Z(MSM6840770003)" . . . . . "Sequential Identification of Microplane Model Parameters"@en . "14"^^ . "978-80-01-03759-1" . "Zeman, Jan" . "3"^^ . . "Sequential Identification of Microplane Model Parameters" . "genetic algorithms; microplane model; neural networks; parameter identification; sensitivity analysis"@en . . . "Postupn\u00E1 identifikace parametr\u016F mikroplo\u0161kov\u00E9ho modelu"@cs . . "105;118" . . "Sequential Identification of Microplane Model Parameters"@en . "Lep\u0161, Mat\u011Bj" . "Zahr\u00E1dky" . . "2007-06-18+02:00"^^ . "A new procedure based on layered feedforward neural networks for the microplane material model parameters identification is proposed in the present paper. It is based on the inverse mode of inverse analysis presented in the Part I. Novelties are usage of the Latin Hypercube Sampling method for the generation of training sets, a sensitivity analysis and a genetic algorithm-based training of a neural network by an evolutionary algorithm. Advantages and disadvantages of this approach together with possible extensions are thoroughly discussed and analyzed."@en . "3"^^ . . "V tomto \u010Dl\u00E1nku je uk\u00E1z\u00E1na nov\u00E1 metoda identifikace parametr\u016F modelu microplane zalo\u017Een\u00E1 na vrstevnat\u00E9 dop\u0159edn\u00E9 neuronov\u00E9 s\u00EDti. Tato metoda je p\u0159\u00EDkladem inverzn\u00EDho postupu inverzn\u00ED anal\u00FDzy, kter\u00FD je pops\u00E1n v \u010D\u00E1sti I tohoto p\u0159\u00EDsp\u011Bvku. Novinkou je pou\u017Eit\u00ED citlivostn\u00ED anal\u00FDzy pro zji\u0161t\u011Bn\u00ED vlivu jednotliv\u00FDch parametr\u016F modelu na chov\u00E1n\u00ED konstrukce, metody Latin Hypercube Sampling p\u0159i p\u0159\u00EDprav\u011B tr\u00E9novac\u00EDch dat pro neuronovou s\u00ED\u0165 a genetick\u00FD algoritmus SADE pou\u017Eit\u00FD pro jej\u00ED tr\u00E9nov\u00E1n\u00ED. V\u00FDhody a nev\u00FDhody navr\u017Een\u00E9ho postupu jsou z\u00E1rove\u0148 s mo\u017En\u00FDmi roz\u0161\u00ED\u0159en\u00EDmi tak\u00E9 podrobn\u011B diskutov\u00E1ny."@cs . "Ku\u010Derov\u00E1, Anna" . "21110" .