A Unifying View of Multivariate State Space Models for Soft Sensors in Industrial Processes-Reference-Cited by-同舟云学术

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A Unifying View of Multivariate State Space Models for Soft Sensors in Industrial Processes

Published:2024 Issue: Volume:12 Page:5920-5932
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Liu Wenyi¹^ORCID,Yairi Takehisa¹^ORCID

Affiliation:

1. Department of Advanced Interdisciplinary Studies, The University of Tokyo, Tokyo, Japan

Funder

China Scholarship Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10366274.pdf?arnumber=10366274

Reference33 articles.

1. Dynamic Generalized Linear Models and Bayesian Forecasting: Rejoinder

2. Variational Bayesian Approach to Nonstationary and Oscillatory Slow Feature Analysis With Applications in Soft Sensing and Process Monitoring

3. A survey on concept drift adaptation

4. A Review on Soft Sensors for Monitoring, Control, and Optimization of Industrial Processes

5. Direct importance estimation with model selection and its application to covariate shift adaptation;Sugiyama

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