| Autor: |
Jinghua Wang, Lei Yan, Taijie Tang, Fang Liu, Jin Cheng |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
E3S Web of Conferences, Vol 300, p 02005 (2021) |
| ISSN: |
2267-1242 |
| Popis: |
With the large-scale and high-intensity mining of coal resources in the Wuhai mining area, the destruction of soil and erosion of rocks has intensified, causing a large amount of surface soil spalling from the mine body and serious damage to the surface vegetation, which has had a serious impact on the quality of the environment in and around the mine. This paper focuses on the corresponding early warning research on air quality in the mining area of Wuhai, and constructs Deep Recurrent Neural Network (DRNN) and Deep Long Short Time Memory Neural Network (DLSTM) air quality prediction models based on the filtered weather factors. The simulation results are also compared and find that the prediction results of DLSTM are better than those of DRNN, with a prediction accuracy of 92.85%. The model is able to accurately predict the values and trends of various air pollutant concentrations in the mining area of Wuhai. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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