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Coal Mining

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Prediction model with multi-point relationship fusion via graph convolutional network: A case study on mining-induced surface subsidence.

PloS one
Accurate prediction of surface subsidence is of significance for analyzing the pattern of mining-induced surface subsidence, and for mining under buildings, railways, and water bodies. To address the problem that the existing prediction models ignore...

Research on state perception of scraper conveyor based on one-dimensional convolutional neural network.

PloS one
Addressing the challenges of current scraper conveyor health assessments being influenced by expert knowledge and the relative difficulty in establishing degradation models for equipment, this study proposed a method for assessing the health status o...

Impact of long-term mining activity on groundwater dynamics in a mining district in Xinjiang coal Mine Base, Northwest China: insight from geochemical fingerprint and machine learning.

Environmental science and pollution research international
Long-term coal mining could lead to a serious of geo-environmental problems. However, less comprehensive identification of factors controlling the groundwater dynamics were involved in previous studies. This study focused on 68 groundwater samples co...

Land subsidence prediction in coal mining using machine learning models and optimization techniques.

Environmental science and pollution research international
Land surface subsidence is an environmental hazard resulting from the extraction of underground resources. In underground mining, when mineral materials are extracted deep within the ground, the emptying or caving of the mined spaces leads to vertica...

[Neural network analysis of mechanization's impact on coal miner's occupational health].

Zhonghua lao dong wei sheng zhi ye bing za zhi = Zhonghua laodong weisheng zhiyebing zazhi = Chinese journal of industrial hygiene and occupational diseases
In order to clarify the transmission mechanism of the impact of mechanization on the occupational health of miners and to provide empirical evidence for the development of new quality productivity in the coal industry that balances health and efficie...

Evaluation of mine ecological environment based on fuzzy hierarchical analysis and grey relational degree.

Environmental research
In order to improve the level of mine ecological environment management and restoration, and to improve and enhance the overall environmental quality of mines. This study takes coal mine as the perspective, and constructs evaluation indexes in two st...

Neuro-fuzzy prediction model of occupational injuries in mining.

International journal of occupational safety and ergonomics : JOSE
This study investigates the possibility of developing a unique model for predicting work-related injuries in Serbian underground coal mines using neural networks and fuzzy logic theory. Accidents are common due to the unique nature of underground mi...

A spatial machine learning approach to exploring the impacts of coal mining and ecological restoration on regional ecosystem health.

Environmental research
Ecosystem health is an important approach to measuring urban and regional sustainability. In previous studies, the spatiotemporal changes of ecosystem health have been addressed using comprehensive assessment index system. However, the quantitative c...

Coal and gas outburst prediction based on data augmentation and neuroevolution.

PloS one
Coal and gas outburst (CGO) is a complicated natural disaster in underground coal mine production. In constructing smart mines, predicting CGO risks efficiently and accurately is necessary. This paper proposes a CGO risk prediction method based on da...

Evaluation of machine learning models for accurate prediction of heavy metals in coal mining region soils in Bangladesh.

Environmental geochemistry and health
Coal mining soils are highly susceptible to heavy metal pollution due to the discharge of mine tailings, overburden dumps, and acid mine drainage. Developing a reliable predictive model for heavy metal concentrations in this region has proven to be a...