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Updated: Jun 7, 2025

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通过实验室规模地震的数值模拟和无监督机器学习来揭示地震核化的洞察力

Sheng Hua Ye1,2, Semechah K Y Lui3,4, R Paul Young5,4

  • 1Civil and Mineral Engineering, University of Toronto, 35 St. George St, Toronto, ON, M5S 1A4, Canada. will.ye@mail.utoronto.ca.

Scientific reports
|November 20, 2024
PubMed
概括

这项研究使用机器学习来分析地震数据,这表明级触发机制和预滑触发机制可能并存. 前方块可以通过增加剪切应力积累来使断层破裂.

关键词:
集群分析分析集群分析这就是为什么DEMEM.地震核化发生的地震.谷物尺度的谷物尺度实验室地震 实验室地震机器学习是机器学习.

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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