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Scientific-Technical Union of Mechanical Engineering

The study of the processes in different real systems is limited to their modelling, i.e. their approximate description by creating models of these systems and processes. Systems and processes models are divided into two classes - physical and mathematical. In recent decades, it has become clear that the notion of mathematical modelling refers equally to systems of another nature - social, economic, and others. In other words, the behavior of different systems can be effectively explored using their mathematical models. It is only necessary to properly choose the appropriate mathematical apparatus. On the other hand, the range of mathematical models is extremely wide - from algebra and logic to functional analysis. This means that the regular direct contacts between engineer researchers and specialists from different fields of mathematics are very important for the advancement of science and technology. For professional mathematicians, these contacts will enable them to better target the needs of representatives of other areas of knowledge. And the more contacts there are the better. One of the most interesting problems of modern science is the development of methods and models for research and optimization of different systems. Thus knowledge is presented in a form that can be used. More and more mathematics is becoming the language of innovation and intelligent technologies and the modern industrial society.

Scientific-Technical Union of Mechanical Engineering;     Tel.: [(+359 2) 987 72 90];     Email: office@mathmodel.eu

Basic principles of mathematical modelling, Analogy principle, Model hierarchy, Methodology of mathematical modelling, System analysis, Mathematical modelling in fundamental and applied physics, mechanics, chemistry and biology, Technological processes as objects of automation, Mathematical methods of management, Modelling of smart production technologies and systems, Virtual technologies and simulations, Information and computer technologies, Robotics, Artificial intellect, Radio electronics, Statistical and stochastic models, Neural networks, Situation modelling,

Mathematische Logik, Grundlagen der Mathematik,    Neuronale Netze und Künstliche Intelligenz, Maschinelles Lernen