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Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis
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关于使用深度决定性政策梯度强化学习在反相液态染色学中用于保留时间建模的观点

Alexander Kensert1, Gert Desmet2, Deirdre Cabooter3

  • 1University of Leuven (KU Leuven), Department for Pharmaceutical and Pharmacological Sciences, Pharmaceutical Analysis, Herestraat 49, 3000 Leuven, Belgium; Vrije Universiteit Brussel, Department of Chemical Engineering, Pleinlaan 2, 1050 Brussel, Belgium.

Journal of chromatography. A
|December 15, 2023
PubMed
概括

强化学习,特别是深度决定性政策梯度算法,可以有效地选择用于液体染色学保留时间建模的侦察运行. 通常,使用Neue-Kuss模型进行精确的保留参数检索,三次侦察运行通常就足够了.

关键词:
梯度化溶解是一种渐变的过程.异分类化异分类化机器学习 机器学习预测的准确性 预测的准确性保留时间建模.

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