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Updated: Jul 24, 2025

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用混合数据分区和离散的同时扰乱进行行为干预的异形动态建模 随机近似

Rachael T Kha1, Daniel E Rivera1, Predrag Klasnja2

  • 1R. T. Kha and D. E. Rivera are with the Control Systems Engineering Lab (CSEL) in the School for Engineering of Matter, Transport and Energy at Arizona State University, Tempe, AZ 85281 USA.

Proceedings of the ... American Control Conference. American Control Conference
|July 10, 2023
PubMed
概括

离散同时扰乱随机近似 (DSPSA) 有效地识别了个性化行为干预模型的特征. 这种方法通过分析个人参与者数据来优化干预,以改善体育活动促进.

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Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
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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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Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

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