DIGITAL ENVIRONMENTAL INVESTMENT FORECAST USING A DECISION TREE MACHINE LEARNING MODEL
Theoretical foundations for the development of environmental protection measures in Russia and the world, the issues of investing in environmental protection are studied. The scientific novelty lies in the fact that based on the use of a variational series of the studied parameters, a machine learni...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Science and Innovation Center Publishing House
2023-03-01
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| Series: | Наука Красноярья |
| Subjects: | |
| Online Access: | http://kras-science.ru/jour/index.php/nk/article/view/166 |
| _version_ | 1797826786856271872 |
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| author | Nikolay I. Lomakin Lyudmila Ya. Solomakhina Victoria V. Pokidova Irina A. Ulanova Alexander N. Kurasov Yury A. Kachanov |
| author_facet | Nikolay I. Lomakin Lyudmila Ya. Solomakhina Victoria V. Pokidova Irina A. Ulanova Alexander N. Kurasov Yury A. Kachanov |
| author_sort | Nikolay I. Lomakin |
| collection | DOAJ |
| description | Theoretical foundations for the development of environmental protection measures in Russia and the world, the issues of investing in environmental protection are studied. The scientific novelty lies in the fact that based on the use of a variational series of the studied parameters, a machine learning model “Decision Tree” was developed, with the help of which a predictive value of the amount of investment in environmental protection measures was formed. The relevance lies in the fact that to determine the volume of investment in environmental measures in the country, an artificial intelligence system was used – machine learning “Decision tree” (ML “Decision tree”), which made it possible to successfully solve a complex problem due to the influence of many factors on the parameter under study. The use of the proposed approach is especially relevant in the light of the May Decrees of the President of the Russian Federation. In 2018, in the Decrees of the President, strategic principles for the development of the country were formulated, aimed at the formation of a “digital economy”, designed to ensure further movement in accordance with the “Strategy for Scientific and Technical Development of Russia” in the main direction, according to which, as a foundation for the implementation of innovative changes in the state will use digital technologies. With the help of the artificial intelligence system, a forecast was formed for such a parameter as the volume of investment in the country in environmental measures for the next year, namely 6.2221 million rubles. |
| first_indexed | 2024-04-09T12:37:48Z |
| format | Article |
| id | doaj.art-9bc6ffaf164f4212956c0642ea56f6cd |
| institution | Directory Open Access Journal |
| issn | 2070-7568 2782-3261 |
| language | English |
| last_indexed | 2024-04-09T12:37:48Z |
| publishDate | 2023-03-01 |
| publisher | Science and Innovation Center Publishing House |
| record_format | Article |
| series | Наука Красноярья |
| spelling | doaj.art-9bc6ffaf164f4212956c0642ea56f6cd2023-05-15T07:43:34ZengScience and Innovation Center Publishing HouseНаука Красноярья2070-75682782-32612023-03-0112115017110.12731/2070-7568-2023-12-1-150-171166DIGITAL ENVIRONMENTAL INVESTMENT FORECAST USING A DECISION TREE MACHINE LEARNING MODELNikolay I. Lomakin0Lyudmila Ya. Solomakhina1Victoria V. Pokidova2Irina A. Ulanova3Alexander N. Kurasov4Yury A. Kachanov5Volgograd State Technical UniversityVolgograd State Technical UniversityVolgograd State Technical UniversityVolgograd State Technical UniversityVolgograd State Technical UniversityVolgograd State Technical UniversityTheoretical foundations for the development of environmental protection measures in Russia and the world, the issues of investing in environmental protection are studied. The scientific novelty lies in the fact that based on the use of a variational series of the studied parameters, a machine learning model “Decision Tree” was developed, with the help of which a predictive value of the amount of investment in environmental protection measures was formed. The relevance lies in the fact that to determine the volume of investment in environmental measures in the country, an artificial intelligence system was used – machine learning “Decision tree” (ML “Decision tree”), which made it possible to successfully solve a complex problem due to the influence of many factors on the parameter under study. The use of the proposed approach is especially relevant in the light of the May Decrees of the President of the Russian Federation. In 2018, in the Decrees of the President, strategic principles for the development of the country were formulated, aimed at the formation of a “digital economy”, designed to ensure further movement in accordance with the “Strategy for Scientific and Technical Development of Russia” in the main direction, according to which, as a foundation for the implementation of innovative changes in the state will use digital technologies. With the help of the artificial intelligence system, a forecast was formed for such a parameter as the volume of investment in the country in environmental measures for the next year, namely 6.2221 million rubles.http://kras-science.ru/jour/index.php/nk/article/view/166mlenvironmental investmentdigital economydecision treedigital forecast |
| spellingShingle | Nikolay I. Lomakin Lyudmila Ya. Solomakhina Victoria V. Pokidova Irina A. Ulanova Alexander N. Kurasov Yury A. Kachanov DIGITAL ENVIRONMENTAL INVESTMENT FORECAST USING A DECISION TREE MACHINE LEARNING MODEL Наука Красноярья ml environmental investment digital economy decision tree digital forecast |
| title | DIGITAL ENVIRONMENTAL INVESTMENT FORECAST USING A DECISION TREE MACHINE LEARNING MODEL |
| title_full | DIGITAL ENVIRONMENTAL INVESTMENT FORECAST USING A DECISION TREE MACHINE LEARNING MODEL |
| title_fullStr | DIGITAL ENVIRONMENTAL INVESTMENT FORECAST USING A DECISION TREE MACHINE LEARNING MODEL |
| title_full_unstemmed | DIGITAL ENVIRONMENTAL INVESTMENT FORECAST USING A DECISION TREE MACHINE LEARNING MODEL |
| title_short | DIGITAL ENVIRONMENTAL INVESTMENT FORECAST USING A DECISION TREE MACHINE LEARNING MODEL |
| title_sort | digital environmental investment forecast using a decision tree machine learning model |
| topic | ml environmental investment digital economy decision tree digital forecast |
| url | http://kras-science.ru/jour/index.php/nk/article/view/166 |
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