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Exploring machine learning techniques for open stope stability prediction:A comparative study and feature importance analysis

Alicja Szmigiel Derek B.Apel Yashar Pourrahimian Hassan Dehghanpour Yuanyuan Pu

Rock Mechanics Bulletin2025，Vol.4Issue(3)：P.39-52,14.

Rock Mechanics Bulletin2025，Vol.4Issue(3)：P.39-52,14.DOI:10.1016/j.rockmb.2024.100146

Exploring machine learning techniques for open stope stability prediction:A comparative study and feature importance analysis

Alicja Szmigiel ¹Derek B.Apel ¹Yashar Pourrahimian ¹Hassan Dehghanpour ¹Yuanyuan Pu²

作者信息

1. University of Alberta,School of Mining and Petroleum Engineering,Edmonton,Alberta,T6G 2R3,Canada
2. Chongqing University,Chongqing,400044,China
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摘要

关键词

Machine learning/Stope stability/Feature importance/Artificial neural network

分类

矿业与冶金

引用本文复制引用

Alicja Szmigiel,Derek B.Apel,Yashar Pourrahimian,Hassan Dehghanpour,Yuanyuan Pu..Exploring machine learning techniques for open stope stability prediction:A comparative study and feature importance analysis[J].Rock Mechanics Bulletin,2025,4(3):P.39-52,14.

基金项目

financially supported by this project:NSERC RGPIN-2019-04572 Apel. （）

Rock Mechanics Bulletin

ISSN：2773-2304

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