研究与来源Uncertainty quantification of deep learning algorithms for mineral prospectivity mapping Geoscientific Model Development · 2026.09.18 论文作者：Ziye Wang · Renguang Zuo DOI: 10.5194/gmd-19-8755-2026 AI 找矿与成矿预测地球系统地球化学与异常识别固体地球数学地质与大数据 本条目提供可追溯的文献信息，尚未发布完整编辑解读。 阅读原始来源 ↗
研究论文Geoscience Data Journal2026.09.21Machine Learning Approaches for Predicting Total Organic Carbon From Petrophysical Well Logs in the Wufeng–Longmaxi Shale, Southeast Sichuan Basin, China暂未提供译文作者 Haseeb Ahmad · Jiang Shu · Naveed Rehman · Muhammad Asad · Muhammad Tariq · Aqib Saeed · Attiqullah Ayaz条目与解读阅读原文 ↗
研究论文Pure and Applied Geophysics2026.09.21Machine Learning–Driven Seismic Vulnerability Assessment of Prefabricated Concrete Beam–Column Joints Using High-Fidelity Simulations暂未提供译文作者 Jinzhou He条目与解读阅读原文 ↗
研究论文Bulletin of Earthquake Engineering2026.04.21Explainable machine learning for ground motion modeling: predictive dominance of energy-based measures in the Southern Turkey seismic sequence暂未提供译文作者 Mohammad Reza Bagerzadeh Karimi条目与解读阅读原文 ↗
研究论文Journal of Seismology2026.08.31Explainable and statistically validated machine learning for earthquake alert-level classification using seismic intensity features暂未提供译文作者 Yıldırım Özüpak条目与解读阅读原文 ↗