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Updated: Jun 7, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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Published on: October 28, 2022

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基于多创新理论和智能优化战略的内核极端学习机器的在线估计方法

Yanjiao Wang1, Yiting Liu1, Weidi Li1

  • 1School of Automation, Guangdong University of Technology, Guangzhou 510006, China.

ISA transactions
|November 13, 2024
PubMed
概括

本研究介绍了新的在线学习模型,即多创新在线顺序极端学习机器 (MIOSELM) 和其内核版本 (MIKOSELM),用于动态数据建模. 这些方法提高了在线计算的适应性和效率,在基准数据集上得到验证.

关键词:
核心极端学习机器学习的核心.多创新理论多创新理论在线学习模式的在线学习模式.参数估计的参数估计.群体情报算法 群体情报算法

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This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
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