In recent years, the mining and utilization of large-scale mineral resources and the promotion of mine reconstruction projects have led to the increasingly serious problems of heavy metal pollution and water pollution (WP) in mine waters, which have posed potential threats to the health of the residents in and around the mines. Therefore, it is of vital importance to study the pollution characteristics of water bodies in mining areas to improve the water environment in mining areas. In this study, three mine alterations are used as the research objects to initially study the current WP status of surface water and groundwater in the watersheds near the mines, and to make a preliminary evaluation of the water environment quality using chaotic neural network algorithm (CNNA), so as to clarify the WP situation under the influence of mine alterations. This study has some application value for the practice of WP prevention and control engineering in mine reconstruction projects.

Jinpeng Wang. Fusion Chaos Neural Network Algorithm to Control Water Pollution Prevention in Mine Reconstruction Projects. Water Pollution Prevention and Control Project (2022), Vol. 3, Issue 4: 20-28. https://doi.org/10.38007/WPPCP.2022.030403.

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