. "9" . . . "Evolutionary identification of dynamical systems"@en . "28140" . "Evolutionary identification of dynamical systems"@en . "3"^^ . . "RIV/70883521:28140/08:63507081" . . . . . "Evolutionary identification of dynamical systems" . . "Synt\u00E9za, identifikace a \u0159\u00EDzen\u00ED komplexn\u00EDch dynamick\u00FDch syst\u00E9m\u016F jsou obvykle velmi komplikovan\u00E9. Klasick\u00E9 metody pot\u0159ebuj\u00ED ur\u010Dit\u00E1 zjednodu\u0161en\u00ED, kter\u00E1 ale vedou k idealizovan\u00FDm \u0159e\u0161en\u00EDm, kter\u00E1 mohou b\u00FDt daleko od reality. Naproti tomu, t\u0159\u00EDda metoda zalo\u017Een\u00FDch na evolu\u010Dn\u00EDch principech jsou \u00FAsp\u011B\u0161n\u011B pou\u017Eity k \u0159e\u0161en\u00ED t\u011Bchto probl\u00E9m\u016F s vysok\u00FDm stupn\u011Bm p\u0159esnosti. V tomto \u010Dl\u00E1nku je p\u0159edvedena nov\u00E1 metoda, kter\u00E1 ji\u017E s \u00FAsp\u011Bchem byla pou\u017Eita nap\u0159. p\u0159i synt\u00E9ze neuronov\u00FDch s\u00EDt\u00ED, elektrick\u00FDch obvod\u016F apod. Evolu\u010Dn\u00ED algoritmy byly pou\u017Eity zde pro identifikaci dynamick\u00FDch syst\u00E9m\u016F."@cs . . "P(GA102/06/1132), Z(MSM7088352101)" . . "GB - Spojen\u00E9 kr\u00E1lovstv\u00ED Velk\u00E9 Brit\u00E1nie a Severn\u00EDho Irska" . "RIV/70883521:28140/08:63507081!RIV09-GA0-28140___" . "dynamic system; identification; evolutionary algorithms"@en . . "Evolu\u010Dn\u00ED identifikace dynamick\u00FDch syst\u00E9m\u016F"@cs . "Synthesis, identification and control of the complex dynamical systems are usually extremely complicated. When classics methods are used, some simplifications are required which tends to lead to idealized solutions that are far away to reality. In contrast, the class of methods based on evolutionary principles is successfully used to solve this kind of problems with a high level of precision. In this paper a novel method is discussed which has been successfully proven in many simulations like neural network synthesis and electrical circuit synthesis. Typical examples are discussed, alongside the use of evolutionary algorithms on dynamical system synthesis - identification."@en . "\u0160enke\u0159\u00EDk, Roman" . . "Evolu\u010Dn\u00ED identifikace dynamick\u00FDch syst\u00E9m\u016F"@cs . . . . "Synthesis, identification and control of the complex dynamical systems are usually extremely complicated. When classics methods are used, some simplifications are required which tends to lead to idealized solutions that are far away to reality. In contrast, the class of methods based on evolutionary principles is successfully used to solve this kind of problems with a high level of precision. In this paper a novel method is discussed which has been successfully proven in many simulations like neural network synthesis and electrical circuit synthesis. Typical examples are discussed, alongside the use of evolutionary algorithms on dynamical system synthesis - identification." . "1473-8031" . "International Journal of Simulation, Systems, Science and Technology" . "Zelinka, Ivan" . . "[7202AE96DB79]" . "Evolutionary identification of dynamical systems" . "3" . "13"^^ . . "366955" . "Oplatkov\u00E1, Zuzana" . "3"^^ . .