Time–space coupled learning method for model reduction of distributed parameter systems with encoder‐decoder and RNN-Reference-Cited by-同舟云学术

Time–space coupled learning method for model reduction of distributed parameter systems with encoder‐decoder and RNN

Published:2020-05-15 Issue:8 Volume:66 Page:
ISSN:0001-1541
Container-title:AIChE Journal
language:en
Short-container-title:AIChE J

Author:

Qing Xiangyun¹^ORCID,Jin Jing¹,Niu Yugang¹,Zhao Shuangliang²^ORCID

Affiliation:

1. Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology), Ministry of EducationEast China University of Science and Technology Shanghai China

2. State Key Laboratory of Chemical Engineering and School of Chemical EngineeringEast China University of Science and Technology Shanghai China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

General Chemical Engineering,Environmental Engineering,Biotechnology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/aic.16251

Reference38 articles.

1. Studies on nonlinear dynamics and control of a tubular reactor with recycle

2. Modeling of distributed parameter systems for applications—A synthesized review from time–space separation

3. New Perspectives in Turbulence

4. An Efficient Electrochemical–Thermal Model for a Lithium-Ion Cell by Using the Proper Orthogonal Decomposition Method

5. Spectral-approximation-based intelligent modeling for distributed thermal processes

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