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Small sample data-driven interpretable artificial neural network computation for two-component chromatographic separation process
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DOI：10.1016/j.chroma.2025.466290.png)
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Abstract
En 中文
• An artificial neural network model for chromatography has been proposed • This model is interpretable and does not belong to black box computing • A network structure for two-component competitive adsorption was provided • This model can be driven by data from several experiments
Keywords:
artificial neural network
chromatography
interpretable model
competitive adsorption
data-driven modeling
Journal
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4
Papers:
3.2W
Citations:
5.0W
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