"The aim of the paper is to demonstrate using of artificial neural networks for the solution of practical problems of the identification of the complex non-linear systems' dynamic behavior. The mathematical model of the hydraulic-pneumatic system was investigated in order to build an alternative of this model, namely in the form of the artificial neural network (ANN). The model presents generally nonlinear multi-dimensional system with two inputs and two outputs. Input variables are flows through controlled pumps and output variables are water levels in the bottom tanks of the system. Both inputs and outputs of the system are represented as unified voltage signals. Solution of the problem consisted in the description of selected single dependences between particular input and output variables by means of ANN. For the problem solution Neural Network Toolbox was used a toolbox of the computing system MATLAB/SIMULINK."@en . . . . . "Um\u011Bl\u00E9 neuronov\u00E9 s\u00EDt\u011B jako prost\u0159edek pro modelov\u00E1n\u00ED dynamick\u00E9ho chov\u00E1n\u00ED hydraulicko-pneumatick\u00E9 soustavy"@cs . "Seidl, Pavel" . "Um\u011Bl\u00E9 neuronov\u00E9 s\u00EDt\u011B jako prost\u0159edek pro modelov\u00E1n\u00ED dynamick\u00E9ho chov\u00E1n\u00ED hydraulicko-pneumatick\u00E9 soustavy" . . . . "RIV/00216275:25530/08:00007218" . "5" . "Taufer, Ivan" . "Z(MSM0021627505)" . . "RIV/00216275:25530/08:00007218!RIV09-MSM-25530___" . "Um\u011Bl\u00E9 neuronov\u00E9 s\u00EDt\u011B jako prost\u0159edek pro modelov\u00E1n\u00ED dynamick\u00E9ho chov\u00E1n\u00ED hydraulicko-pneumatick\u00E9 soustavy" . "10"^^ . "[F12DC9DB5EFF]" . "C\u00EDlem uveden\u00E9ho p\u0159\u00EDsp\u011Bvku je demonstrovat pou\u017Eit\u00ED um\u011Bl\u00FDch neuronov\u00FDch s\u00EDt\u00ED k \u0159e\u0161en\u00ED praktick\u00FDch \u00FAloh identifikace dynamick\u00E9ho chov\u00E1n\u00ED slo\u017Eit\u00FDch neline\u00E1rn\u00EDch soustav. Byl zkoum\u00E1n matematicko-fyzik\u00E1ln\u00ED model hydraulicko-pneumatick\u00E9 soustavy za \u00FA\u010Delem vytvo\u0159en\u00ED alternativy tohoto modelu, a to ve tvaru um\u011Bl\u00E9 neuronov\u00E9 s\u00EDt\u011B (UNS). Model p\u0159edstavuje obecn\u011B neline\u00E1rn\u00ED v\u00EDcerozm\u011Brnou soustavu se dv\u011Bma vstupy a dv\u011Bma v\u00FDstupy. P\u0159i\u010Dem\u017E vstupn\u00EDmi veli\u010Dinami jsou pr\u016Ftoky \u010Derpadly a v\u00FDstupn\u00EDmi veli\u010Dinami jsou v\u00FD\u0161ky hladin v doln\u00EDch n\u00E1dr\u017E\u00EDch soustavy. Vstupy i v\u00FDstupy soustavy jsou reprezentov\u00E1ny unifikovan\u00FDmi nap\u011B\u0165ov\u00FDmi sign\u00E1ly. \u0158e\u0161en\u00ED \u00FAlohy spo\u010D\u00EDvalo v popisu jednotliv\u00FDch z\u00E1vislost\u00ED mezi konkr\u00E9tn\u00EDmi vstupn\u00EDmi a v\u00FDstupn\u00EDmi veli\u010Dinami pomoc\u00ED UNS. K \u0159e\u0161en\u00ED \u00FAlohy byl pou\u017Eit Neural Network Toolbox v\u00FDpo\u010Detn\u00EDho syst\u00E9mu MATLAB/SIMULINK."@cs . "USING OF ARTIFICIAL NEURAL NETWORK FOR THE IDENTIFICATION OF DYNAMIC PROPERTIES OF HYDRAULIC-PNEUMATIC SYSTEM"@en . "2"^^ . "CZ - \u010Cesk\u00E1 republika" . "Artificial Neural Networks; Continual Bioreactor; Internal Model Control"@en . "C\u00EDlem uveden\u00E9ho p\u0159\u00EDsp\u011Bvku je demonstrovat pou\u017Eit\u00ED um\u011Bl\u00FDch neuronov\u00FDch s\u00EDt\u00ED k \u0159e\u0161en\u00ED praktick\u00FDch \u00FAloh identifikace dynamick\u00E9ho chov\u00E1n\u00ED slo\u017Eit\u00FDch neline\u00E1rn\u00EDch soustav. Byl zkoum\u00E1n matematicko-fyzik\u00E1ln\u00ED model hydraulicko-pneumatick\u00E9 soustavy za \u00FA\u010Delem vytvo\u0159en\u00ED alternativy tohoto modelu, a to ve tvaru um\u011Bl\u00E9 neuronov\u00E9 s\u00EDt\u011B (UNS). Model p\u0159edstavuje obecn\u011B neline\u00E1rn\u00ED v\u00EDcerozm\u011Brnou soustavu se dv\u011Bma vstupy a dv\u011Bma v\u00FDstupy. P\u0159i\u010Dem\u017E vstupn\u00EDmi veli\u010Dinami jsou pr\u016Ftoky \u010Derpadly a v\u00FDstupn\u00EDmi veli\u010Dinami jsou v\u00FD\u0161ky hladin v doln\u00EDch n\u00E1dr\u017E\u00EDch soustavy. Vstupy i v\u00FDstupy soustavy jsou reprezentov\u00E1ny unifikovan\u00FDmi nap\u011B\u0165ov\u00FDmi sign\u00E1ly. \u0158e\u0161en\u00ED \u00FAlohy spo\u010D\u00EDvalo v popisu jednotliv\u00FDch z\u00E1vislost\u00ED mezi konkr\u00E9tn\u00EDmi vstupn\u00EDmi a v\u00FDstupn\u00EDmi veli\u010Dinami pomoc\u00ED UNS. K \u0159e\u0161en\u00ED \u00FAlohy byl pou\u017Eit Neural Network Toolbox v\u00FDpo\u010Detn\u00EDho syst\u00E9mu MATLAB/SIMULINK." . "401344" . . . . "Um\u011Bl\u00E9 neuronov\u00E9 s\u00EDt\u011B jako prost\u0159edek pro modelov\u00E1n\u00ED dynamick\u00E9ho chov\u00E1n\u00ED hydraulicko-pneumatick\u00E9 soustavy"@cs . "Perner\u00B4s Contacts" . "2"^^ . . . "USING OF ARTIFICIAL NEURAL NETWORK FOR THE IDENTIFICATION OF DYNAMIC PROPERTIES OF HYDRAULIC-PNEUMATIC SYSTEM"@en . "3" . . . . "1801-674X" . "25530" .