Integrated Deep Learning Framework Predicts Underground Hazards in Smart Mine Testing
Researchers have developed a multi-model deep learning architecture that achieved 98.76 percent accuracy in detecting hazards and assessing risks across ...
Researchers have developed a multi-model deep learning architecture that achieved 98.76 percent accuracy in detecting hazards and assessing risks across ...
A new method uses drilling vibration and pressure signals to identify weak roof zones in coal mines, validated by laboratory ...
A systematic scoping review of 50 studies finds that academic IoT and LoRa/LoRaWAN research for mine safety is concentrated at ...
A coupled numerical simulation shows coal mining beneath uranium-bearing strata can raise aquitard permeability by two orders of magnitude, allowing ...
Researchers have revealed how clusters of abandoned roadways destabilize narrow coal pillars and overlying roof blocks in extra-thick coal seams, ...
Researchers combined grey wolf optimization with support vector regression to predict coal spontaneous combustion temperatures with over 99 percent accuracy, ...
New experiments and numerical modeling show that the spherical particle assumption systematically overestimates gas diffusion in coal, with an ellipsoidal ...
A Chinese research team has combined COMSOL numerical simulation with an optimized XGBoost-LSTM hybrid machine learning model to predict coal ...
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© 2026 Scienmag - Science Magazine