E3S Web Conf.
Volume 300, 20212021 2nd International Conference on Energy, Power and Environmental System Engineering (ICEPESE2021)
|Number of page(s)||6|
|Section||Environmental System Engineering|
|Published online||06 August 2021|
Research on the air quality prediction model of Wuhai mining area based on deep learning
School of Technology, Beijing Forestry University, Beijing 100083, China
2 College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China
* Corresponding author: email@example.com
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.
© The Authors, published by EDP Sciences, 2021
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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