"2"^^ . "[638E80918AF4]" . "Standardn\u00ED z\u00E1klad komunika\u010Dn\u00EDch s\u00EDt\u00ED p\u0159edstavuj\u00ED aktivn\u00ED prvky, kter\u00E9 prov\u00E1d\u00ED zpracov\u00E1n\u00ED p\u0159en\u00E1\u0161en\u00FDch datov\u00FDch jednotek a na z\u00E1klad\u011B v\u00FDsledk\u016F zpracov\u00E1n\u00ED p\u0159ed\u00E1vaj\u00ED datov\u00E9 jednotky sm\u011Brem od odes\u00EDlatele k p\u0159\u00EDjemci. Nejt\u011B\u017E\u0161\u00EDm \u00FAkolem aktivn\u00EDch prvk\u016F v sou\u010Dasn\u00E9 dob\u011B je ur\u010Den\u00ED, v jak\u00E9m \u010Dasov\u00E9m okam\u017Eiku a kterou datovou jednotku m\u00E1 syst\u00E9m zpracovat, aby zpracov\u00E1n\u00ED odpov\u00EDdalo priorit\u011B p\u0159id\u011Blen\u00E9 jednotliv\u00FDm datov\u00FDm jednotk\u00E1m. Na z\u00E1klad\u011B anal\u00FDzy architektury a funkc\u00ED aktivn\u00EDch s\u00ED\u0165ov\u00FDch prvk\u016F a algoritm\u016F um\u011Bl\u00FDch neuronov\u00FDch s\u00EDt\u00ED lze p\u0159edpokl\u00E1dat efektivn\u00ED vyu\u017Eit\u00ED neuronov\u00FDch s\u00EDt\u00ED pro \u0159\u00EDzen\u00ED s\u00ED\u0165ov\u00FDch prvk\u016F. Tento \u010Dl\u00E1nek je zam\u011B\u0159en na n\u00E1vrh a pou\u017Eit\u00ED vybran\u00E9ho typu um\u011Bl\u00E9 neuronov\u00E9 s\u00EDt\u011B (Hopfieldova neuronov\u00E1 s\u00ED\u0165) pro optim\u00E1ln\u00ED \u0159\u00EDzen\u00ED s\u00ED\u0165ov\u00E9ho p\u0159ep\u00EDna\u010De."@cs . "Modern\u00ED metody pro optimalizaci p\u0159ep\u00EDn\u00E1n\u00ED v po\u010D\u00EDta\u010Dov\u00FDch s\u00EDt\u00EDch"@cs . . "Progressive optimization methods for applied in computer network"@en . "active network element, algorithm, Hopfield neural network, switch"@en . "CZ - \u010Cesk\u00E1 republika" . . . . . "6" . "26210" . "Cepl, Miroslav" . "2009" . . . "Modern\u00ED metody pro optimalizaci p\u0159ep\u00EDn\u00E1n\u00ED v po\u010D\u00EDta\u010Dov\u00FDch s\u00EDt\u00EDch" . . "Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis" . . . "Modern\u00ED metody pro optimalizaci p\u0159ep\u00EDn\u00E1n\u00ED v po\u010D\u00EDta\u010Dov\u00FDch s\u00EDt\u00EDch" . . . "Standard core of communications' networks is represent by active elements, which carries out the processing of transmitted data units. Based on the results of the processing the data are transmitted from sender to recipient. The hardest challenge of the active elements present to determine what the data processing unit and what time of the system to match the processing priority assigned to individual data units. Based on the analysis of the architecture and function of active network components and algorithms, artificial neural networks can be assumed to be effectively useable to manage network elements. This article focuses on the design and use of the selected type of artificial neural network (Hopfield neural network) for the optimal management of network switch."@en . "Modern\u00ED metody pro optimalizaci p\u0159ep\u00EDn\u00E1n\u00ED v po\u010D\u00EDta\u010Dov\u00FDch s\u00EDt\u00EDch"@cs . "Progressive optimization methods for applied in computer network"@en . . . "\u0160\u0165astn\u00FD, Ji\u0159\u00ED" . "5"^^ . "327052" . . "RIV/00216305:26210/09:PU86179" . . "P(GA102/07/1503), Z(MSM0021630529), Z(MSM6215648904)" . "1"^^ . . "RIV/00216305:26210/09:PU86179!RIV12-MSM-26210___" . . "Standardn\u00ED z\u00E1klad komunika\u010Dn\u00EDch s\u00EDt\u00ED p\u0159edstavuj\u00ED aktivn\u00ED prvky, kter\u00E9 prov\u00E1d\u00ED zpracov\u00E1n\u00ED p\u0159en\u00E1\u0161en\u00FDch datov\u00FDch jednotek a na z\u00E1klad\u011B v\u00FDsledk\u016F zpracov\u00E1n\u00ED p\u0159ed\u00E1vaj\u00ED datov\u00E9 jednotky sm\u011Brem od odes\u00EDlatele k p\u0159\u00EDjemci. Nejt\u011B\u017E\u0161\u00EDm \u00FAkolem aktivn\u00EDch prvk\u016F v sou\u010Dasn\u00E9 dob\u011B je ur\u010Den\u00ED, v jak\u00E9m \u010Dasov\u00E9m okam\u017Eiku a kterou datovou jednotku m\u00E1 syst\u00E9m zpracovat, aby zpracov\u00E1n\u00ED odpov\u00EDdalo priorit\u011B p\u0159id\u011Blen\u00E9 jednotliv\u00FDm datov\u00FDm jednotk\u00E1m. Na z\u00E1klad\u011B anal\u00FDzy architektury a funkc\u00ED aktivn\u00EDch s\u00ED\u0165ov\u00FDch prvk\u016F a algoritm\u016F um\u011Bl\u00FDch neuronov\u00FDch s\u00EDt\u00ED lze p\u0159edpokl\u00E1dat efektivn\u00ED vyu\u017Eit\u00ED neuronov\u00FDch s\u00EDt\u00ED pro \u0159\u00EDzen\u00ED s\u00ED\u0165ov\u00FDch prvk\u016F. Tento \u010Dl\u00E1nek je zam\u011B\u0159en na n\u00E1vrh a pou\u017Eit\u00ED vybran\u00E9ho typu um\u011Bl\u00E9 neuronov\u00E9 s\u00EDt\u011B (Hopfieldova neuronov\u00E1 s\u00ED\u0165) pro optim\u00E1ln\u00ED \u0159\u00EDzen\u00ED s\u00ED\u0165ov\u00E9ho p\u0159ep\u00EDna\u010De." . "1211-8516" . .