Practical neural network applications in the mining industry

Abstract

The mining industry relies heavily upon empirical analysis for design and prediction. Neural networks are computer programs that use parallel processing, similar to the human brain, to analyze data for trends and correlation. Two practical neural network applications in the mining industry would be rockburst prediction and stope dilution estimates. This paper summarizes neural network data analysis results for a 1995 Goldcorp/Canmet study on rockbursting and a 1986 UBC/Canmet study on open stope dilution at the Ruttan Mine.