Issue |
E3S Web Conf.
Volume 460, 2023
International Scientific Conference on Biotechnology and Food Technology (BFT-2023)
|
|
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Article Number | 04030 | |
Number of page(s) | 10 | |
Section | IoT, Big Data and AI in Food Industry | |
DOI | https://doi.org/10.1051/e3sconf/202346004030 | |
Published online | 11 December 2023 |
Model for selecting available technologies based on optimality criteria under risk conditions
1 Emperor Alexander I St. Petersburg State Transport University, Department of Water Supply, Sewerage and Hydraulics, Moskovskij prospect, 9, 190031 St. Petersburg, Russian Federation
2 Emperor Alexander I St. Petersburg State Transport University, Department of Higher Mathematics, Sewerage and Hydraulics, Moskovskij prospect, 9, 190031 St. Petersburg, Russian Federation
* Corresponding author: rusanovaev@mail.ru
In today's rapidly developing technologies and materials, the problem of their use is especially relevant. This is primarily due to the possibility of qualitative import substitution in the domestic industry of materials that have been produced abroad for many decades. The paper proposes a mathematical model for selecting the best technology on the example of samples of ash foam concrete, based on the application of optimality criteria set on finite sets - factors (technical characteristics of objects) and alternatives (materials of different chemical composition and physical purpose). Based on the suggested model, a calculation method has been developed to standardize the materials that are used in geo-ecoprotective technologies in accordance with the technical requirements of the clients. This methodology makes it possible to make decisions about the scale of production and implementation based on monitoring data on the use of technology over a long period of operation. The choice of specific technologies from among the many technologies under consideration usually has long-term consequences on environmental safety and economic efficiency and benefits.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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