Artificial Neural Networks for fault prediction


Artificial Neural Networks (ANNs) assess normal, affected and fault zones to predict the risk of floods. This is particularly important for safety and production in mines, where even small faults can weaken the rock resistance and create an escape route for water. ANNs replicate the pattern-finding abilities of the human mind and process data for key factors like vein depth and width, accumulated gas quantities, input changes and degree of fragmentation. These factors are then integrated into a 99% accurate model that can predict a risk of flooding in small geological faults.

Problems solved

Small geological faults weaken the rock resistance and create escape for underground water


Better prediction of faults


3D modelling
big data
flood prevention
machine learning
metals and mining
ore base modelling
risk management

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