APPLICATION OF ARTIFICIAL NEURAL NETWORKS AND ACHIEVEMENTS OF TECHNOLOGICAL RE-ENGINEERING OF MODERN INDUSTRIAL PRODUCTION

Abstract

The article deals with the issue of the justification mechanism for the choice of directions of technological reengineering. It was determined that the effectiveness of the transformations primarily depends on the methods, tools for choosing directions for the radical transformation of the technological basis of the production enterprise and, in general, on the technological policy. The justification of the directions of technological training engineering is connected with a large volume of interdependent variables of innovative transformations and requires a fundamental analysis of their behaviour and impact on production process. Today, neural networks are one of the most famous and effective tools for intelligent data analysis, which is developed thanks to achievements in the field of artificial intelligence theory and computer science. Intelligent systems based on artificial neural networks and fuzzy logic allow solving the tasks of forecasting, optimization, pattern recognition and management. To train the network, it is necessary to have a set of values of input values (factors) and corresponding to each separate set of values of the desired output value. Such an approach completely coincides with the tasks of choosing the directions of technological reengineering at the enterprises of the innovation cluster. For this purpose, significant external and internal factors influencing the effectiveness of the cluster policy have been determined. In contrast to internal, external to the greatest extent allow solving the tasks of forecasting, optimization, pattern recognition and management. In the conditions of an imperfect regional innovation system and taking into account this factor, for the efficiency of solving the tasks of technological reengineering of industrial production, a methodology is proposed that combines foresight forecasting of the prospects of technological reengineering of enterprises with the theory of artificial neural networks. The mechanism of interaction of artificial neural networks and the foresight method in determining directions of technological reengineering based on regional cluster policy are proposed.