Intelligent Prediction of Rock Drillability Using Mesoscopic Structure and Ensemble Learning
收藏中国科学数据2026-04-28 更新2026-04-25 收录
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https://www.sciengine.com/AA/doi/10.15898/j.ykcs.202411080234
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HIGHLIGHTS (1) A feature set with 21 microstructural parameters for rock thin-section particles was proposed, and three feature engineering methods were employed to construct a highly correlated drillability dataset. (2) An intelligent prediction methodology for rock drillability was developed using ensemble learning, where base learners were optimized via the Stacking fusion model. (3) Based on the mesostructural feature set and ensemble learning model, completed feature calculation and drillability prediction were accomplished within 1 min with 14.1% error.
创建时间：
2026-04-28
