Batch Process Modeling with Few-Shot Learning
نویسندگان
چکیده
Batch processes in the biopharmaceutical and chemical manufacturing industries often develop new products to meet changing market demands. When dynamic models of these are trained, modeling with limited data for each product can lead inaccurate results. One solution is extract useful knowledge from past historical production that be applied a grade. In this way, model built quickly without having wait additional data. study, subspace identification combined common feature learning scheme proposed learn The modified state-space contains special parameter matrices. Past batch used train Then, parameters directly transferred into SID grade product. well trained even though there effectiveness algorithm demonstrated numerical example case an industrial penicillin process. cases, extraction framework achieve higher performance multi-input multi-output process regression problem.
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ژورنال
عنوان ژورنال: Processes
سال: 2023
ISSN: ['2227-9717']
DOI: https://doi.org/10.3390/pr11051481