神经网络在采矿业中的实际应用

Proceedings of the Second International Conference on Intelligent Processing and Manufacturing of Materials. IPMM'99 (Cat. No.99EX296) Pub Date : 1999-07-10 DOI:10.1109/IPMM.1999.791515

L. Miller-Tait, R. Pakalnis

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引用次数: 2

摘要

采矿业在设计和预测方面严重依赖实证分析。神经网络是一种计算机程序，它使用类似于人类大脑的并行处理来分析数据的趋势和相关性。神经网络在采矿业中的两个实际应用是岩爆预测和采场贫化估计。本文总结了1995年Goldcorp/Canmet岩爆研究和1986年UBC/Canmet露天矿贫化研究的神经网络数据分析结果。

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Practical neural network applications in the mining industry

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.

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Proceedings of the Second International Conference on Intelligent Processing and Manufacturing of Materials. IPMM'99 (Cat. No.99EX296)

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