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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

岩石力学通报（英文）2025，Vol.4Issue(3)：39-52,14.

岩石力学通报（英文）2025，Vol.4Issue(3)：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

Key words

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

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].岩石力学通报（英文）,2025,4(3):39-52,14.

基金项目

The Natural Sciences and Engineering Research Council of Canada(NSERC)Discovery grant is financially supported by this project:NSERC RGPIN-2019-04572 Apel.The authors are grateful for their support. （NSERC）

岩石力学通报（英文）

ISSN：2773-2304

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