INCREASE OF THE ENERGY-SATURATED MATERIALS EFFICIENCY FOR DEVELOPMENT OF BITUMINOUS OIL DEPOSITS DUE TO THE USE OF MODERN INFORMATION TECHNOLOGIES
UDC: 004.855.5:004.942
DOI: 10.33285/0132-2222-2021-6(575)-19-22
Authors:
MUKHUTDINOV AGLYAM RASHIDOVICH 1,
EFIMOV MAKSIM GENNADIEVICH 1,
VAKHIDOVA ZULFIYA RASHIDOVNA 2
1 Kazan National Research Technological University (KNRTU), Kazan, Russian Federation
2 University of Management "TISBI", Kazan, Russian Federation
Keywords: neural network model, combustible material, optimization, software module, knowledge base, optimal composition, information technology
Annotation:
It is known that one of the most progressive methods of studying complex systems is computer mathematical modeling. Therefore, a promising way to solve such problems is to use the universal computing capabilities of modern software tools based on artificial neural networks (ANN), which have the broadest capabilities of modeling such systems. They allow, based on empirical experience alone, to build neural network models that facilitate the extraction of knowledge from the data and identify previously unknown and never studied dependencies and patterns, actively use them to solve specific practical problems. That’s why, the study of the possibility of using the created neural network model of the combustion process of combustible material and the developed intelligent software module based on modern information technologies in order to optimize its composition to achieve the maximum heating temperature of the bituminous layer is an urgent task. The authors of the paper, using modern computer technologies, have developed an applied software module that allows, on the basis of the developed algorithm and neural network model, determining the optimal composition of the combustible material for maximum heating of the bituminous formation. The possibility of neural network modeling of the combustion process of combustible material from various components is shown. The forecast of the output parameter on a pre-trained network, with a relative error of 6 %, is clearly demonstrated using the knowledge base. It has been established that the solution of the problem associated with finding the optimal composition of the combustible material to ensure the maximum heating temperature of the bituminous layer through neural network modeling of the process of its combustion on the basis of modern information technologies is a promising and urgent direction.
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