Evidence map›Paper›PMID 39696295›Full record

ArticleBMC biotechnology2024

Soft sensor modeling method for Pichia pastoris fermentation process based on substructure domain transfer learning.

Bo Wang, Jun Wei, Le Zhang, Hui Jiang, Cheng Jin, Shaowen Huang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Bo WangKey Laboratory of Agricultural Measurement and Control Technology and Equipment for Mechanical Industrial Facilities, School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, 212013, China.
Jun WeiKey Laboratory of Agricultural Measurement and Control Technology and Equipment for Mechanical Industrial Facilities, School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, 212013, China. 2222207065@stmail.ujs.edu.cn.
Le ZhangWuxi Key Laboratory of Intelligent Robot and Special Equipment Technology, Wuxi Taihu University, Wuxi, 214064, China.
Hui JiangKey Laboratory of Agricultural Measurement and Control Technology and Equipment for Mechanical Industrial Facilities, School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, 212013, China.
Cheng JinWuxi Key Laboratory of Intelligent Robot and Special Equipment Technology, Wuxi Taihu University, Wuxi, 214064, China.
Shaowen HuangKey Laboratory of Agricultural Measurement and Control Technology and Equipment for Mechanical Industrial Facilities, School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, 212013, China.

Funding

the Natural Science Foundation of China NO. 61705093the Natural Science Foundation of the Jiangsu higher Education Institutions of China NO.24KJA510011Wuxi "Light of Tai Lake" Science and Technology Project NO.K20221054
6 · The paper itself

Abstract

backgroundAiming at the problem that traditional transfer methods are prone to lose data information in the overall domain-level transfer, and it is difficult to achieve the perfect match between source and target domains, thus reducing the accuracy of the soft sensor model.

methodsThis paper proposes a soft sensor modeling method based on the transfer modeling framework of substructure domain. Firstly, the Gaussian mixture model clustering algorithm is used to extract local information, cluster the source and target domains into multiple substructure domains, and adaptively weight the substructure domains according to the distances between the sub-source domains and sub-target domains. Secondly, the optimal subspace domain adaptation method integrating multiple metrics is used to obtain the optimal projection matrices

resultsTaking Pichia pastoris fermentation to produce inulinase as an example, the simulation results verify that the root mean square error of the proposed soft sensor model in predicting Pichia pastoris concentration and inulinase concentration is reduced by 48.7% and 54.9%, respectively.

conclusionThe proposed soft sensor modeling method can accurately predict Pichia pastoris concentration and inulinase concentration online under different working conditions, and has higher prediction accuracy than the traditional soft sensor modeling method.

Indexed as

FermentationAlgorithmsSaccharomycetalesSupport Vector MachinePichia pastorisSoft sensorSubstructure domainTransfer learning

Identifiers

PMID39696295
PMCPMC11653563

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.