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

ABSTRACT:

Background

Aiming 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.

Methods

This 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

SUBMITTER: Wang B 

PROVIDER: S-EPMC11653563 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature