Angelika MORGOEVA
Biographic Data
| ID | 9424836 |
|---|---|
| NAME | Angelika MORGOEVA |
| GIVEN NAMES | Angelika |
| FAMILY NAME | MORGOEVA |
| SIGNATURE | MORGOEVA A |
| ORCID | 0000-0003-2949-1993 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Research of the pollutants distribution contained in the waste from the enrichment of a decommissioned tailings pool
Introduction. Monitoring of decommissioned tailings storage facilities is necessary to ensure environmental and technological safety in order to develop protective measures to reduce the potential impact of the tailings storage facility on the environment and to address the issue of additional extraction of valuable components from the tailings. The aim of the research is to investigate of tailings pollutant data to reduce elemental distribution …
Machine learning models study for assessing the effect of coal mining and energy enterprises on ecosystems
Introduction. The development of coal - fired mining and energy enterprises leads to a significant increase in ecosystem pollution. Emissions from coal - fired power plants pose a health hazard to humans, since when coal is burned, pollutants are released from the chimney into the atmosphere and carried by the wind over significant distances. These emissions contain elements and compounds such as Hg, Pb, N2O, SO2, solid particles and various heav…
Development of a hybrid model for predicting the consumption of electrical energy for a mining and metallurgical enterprise
Introduction. Reducing the energy intensity of production is one of the directions of development of enterprises, regions, states, as it affects the level of economic development and environmental well-being. One of the methods that contribute to the rationalization of the use of electric energy is forecasting. The purpose of the study is to develop a model for forecasting electricity consumption, which allows obtaining a reliable forecast of ele…
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Development of a hybrid model for predicting the consumption of electrical energy for a mining and metallurgical enterprise
Introduction. Reducing the energy intensity of production is one of the directions of development of enterprises, regions, states, as it affects the level of economic development and environmental well-being. One of the methods that contribute to the rationalization of the use of electric energy is forecasting. The purpose of the study is to develop a model for forecasting electricity consumption, which allows obtaining a reliable forecast of ele…
Machine learning models study for assessing the effect of coal mining and energy enterprises on ecosystems
Introduction. The development of coal - fired mining and energy enterprises leads to a significant increase in ecosystem pollution. Emissions from coal - fired power plants pose a health hazard to humans, since when coal is burned, pollutants are released from the chimney into the atmosphere and carried by the wind over significant distances. These emissions contain elements and compounds such as Hg, Pb, N2O, SO2, solid particles and various heav…
Research of the pollutants distribution contained in the waste from the enrichment of a decommissioned tailings pool
Introduction. Monitoring of decommissioned tailings storage facilities is necessary to ensure environmental and technological safety in order to develop protective measures to reduce the potential impact of the tailings storage facility on the environment and to address the issue of additional extraction of valuable components from the tailings. The aim of the research is to investigate of tailings pollutant data to reduce elemental distribution …
Engineering (2 works) · Engineering and Environmental Studies (2 works) · Industrial Engineering and Technologies (2 works) · Mining and Gasification Technologies (2 works) · Artificial Intelligence (1 work) · Artificial neural network (1 work) · Autoregressive integrated moving average (1 work) · Business (1 work) · Coal (1 work) · Coal mining (1 work)