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Risk Assessment for a Twin-Screw Granulation Process Using a Supervised Physics-Constrained Auto-encoder and Support Vector Machine Framework

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第一作者： Sampat, Chaitanya

作者： Sampat, Chaitanya ^[1] ; Ramachandran, Rohit

作者单位： Rutgers State University New Brunswick,Rutgers State Univ ^[1]

关键词 physics-constrained supervised auto-encoders quality-by-Design (QbD)quality risk management twin-screw granulation RESIDENCE TIME DISTRIBUTION WET GRANULATION HIGH-SHEAR PROCESS PARAMETERS STOCHASTIC-MODEL DEM ANALYSIS QUALITY AUTOENCODERS ATTRIBUTES NETWORK

发布时间 2023-02-04

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Pharmaceutical research

2022年39卷9期

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Pharmaceutical research

2022年39卷9期

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Risk Assessment for a Twin-Screw Granulation Process Using a Supervised Physics-Constrained Auto-encoder and Support Vector Machine Framework

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Risk Assessment for a Twin-Screw Granulation Process Using a Supervised Physics-Constrained Auto-encoder and Support Vector Machine Framework

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