• Introduction to systems modelling, forms of description of dynamic system.
• Basic types of modelling (physical, mathematical, cybernetic).
• Identification in the process of knowledge and in the process of control. Precarious and aposteriori information about identify system.
• Classification of mathematical model. Identification of structure and of parameters systems.
• Identification methods. Identification of mathematical - physical analysis method.
• Experimental method identification. Deterministic method identification.
• Systems modelling by kind of similarities (mathematical, physical, mathematically- physical, cybernetic). Principle and common of description equational and of block oriented simulation programmes.
• Classification models according to different standpoints. Mathematical simulation, analyst and experimental method recognition of mathematical system description.
• Unconventional simulation - artificial intelligence (fuzzy model, expert model, model neuronal nets, genetic algorithm).
• Model neuronal nets. Usage neuronal nets for simulation choice of technological process.
• Basic types of modelling (physical, mathematical, cybernetic).
• Identification in the process of knowledge and in the process of control. Precarious and aposteriori information about identify system.
• Classification of mathematical model. Identification of structure and of parameters systems.
• Identification methods. Identification of mathematical - physical analysis method.
• Experimental method identification. Deterministic method identification.
• Systems modelling by kind of similarities (mathematical, physical, mathematically- physical, cybernetic). Principle and common of description equational and of block oriented simulation programmes.
• Classification models according to different standpoints. Mathematical simulation, analyst and experimental method recognition of mathematical system description.
• Unconventional simulation - artificial intelligence (fuzzy model, expert model, model neuronal nets, genetic algorithm).
• Model neuronal nets. Usage neuronal nets for simulation choice of technological process.