Guest Editorial: Scientific and Physics-Informed Machine Learning for Industrial Applications-Reference-Cited by-同舟云学术

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Guest Editorial: Scientific and Physics-Informed Machine Learning for Industrial Applications

Published:2023-02 Issue:2 Volume:19 Page:2161-2164
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

Piccialli Francesco¹^ORCID,Giampaolo Fabio¹^ORCID,Camacho David²^ORCID,Mei Gang³^ORCID

Affiliation:

1. Department of Mathematics and Applications “R. Caccioppoli,”, University of Naples Federico II, Napoli, Italy

2. Department of Computer Systems Engineering, Universidad Politécnica de Madrid, Madrid, Spain

3. School of Engineering and Technology, China University of Geosciences (Beijing), Beijing, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/9424/9989328/09925073.pdf?arnumber=9925073

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A PINN-Based Lifetime Predictor for Oil-Impregnated Paper Insulation Degradation in Power Transformers Using Degree of Polymerization;2024 IEEE 18th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG);2024-06-24

2. Quantitative analysis and modification of dynamic p-y curve model for offshore wind turbines considering earthquake history effect based on deep learning;Ocean Engineering;2024-05

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