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Updated: Jul 19, 2026

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一种参数自适应的EEFO VMD方法,以减轻爆炸振动信号的噪音和趋势干扰

Zhenyang Xu1, Zuofu Zhang1, Fuqiang Ren2

  • 1School of Mining Engineering, University of Science and Technology LiaoNing, Anshan, 114051, China.

Scientific reports
|March 24, 2025
PubMed
概括

一种使用自适应变化模式分解 (VMD) 与电捕食优化 (EEFO) 的新方法有效地消除了爆炸振动信号的噪音和趋势干扰. 这种增强的信号处理可以提高复杂环境的分析准确性.

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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.
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