Evaluation of Rockburst Potential in Kimberlite Using Fruit Fly Optimization Algorithm and Generalized Regression Neural Networks
Author:
Publisher
Polish Academy of Sciences Chancellery
Subject
Geochemistry and Petrology,Geotechnical Engineering and Engineering Geology
Link
https://journals.pan.pl/Content/112269/PDF/Archiwum-64-2-04-Apel.pdf
Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Rockburst Prediction and Evaluation Model for Hard Rock Engineering Based on Extreme Gradient Boosting Ensemble Learning and SHAP Value;Geotechnical and Geological Engineering;2023-07-13
2. Mining safety research in China: Understanding safety research trends and future demands for sustainable mining industry;Resources Policy;2023-06
3. A systematic review on fruit fly optimization algorithm and its applications;Artificial Intelligence Review;2023-03-31
4. Assessment of rockburst risk using multivariate adaptive regression splines and deep forest model;Acta Geotechnica;2021-07-26
5. Short-term rockburst risk prediction using ensemble learning methods;Natural Hazards;2020-08-28
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