Prediction of Porosity in Atmospheric Plasma Sprayed Thermal Barrier Coatings Using Terahertz Pulse and Hybrid Machine Learning Algorithms-Reference-Cited by-同舟云学术

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Prediction of Porosity in Atmospheric Plasma Sprayed Thermal Barrier Coatings Using Terahertz Pulse and Hybrid Machine Learning Algorithms

Published:2024 Issue: Volume: Page:1-8
ISSN:0093-3813
Container-title:IEEE Transactions on Plasma Science
language:
Short-container-title:IEEE Trans. Plasma Sci.

Author:

Liu Longhai¹^ORCID,Li Rui²,Ye Dongdong²,Yao Jianquan¹^ORCID

Affiliation:

1. Ministry of Education, School of Precision Instruments and Opto-Electronics Engineering, Key Laboratory of Opto-Electronics Information Technology, Tianjin University, Tianjin, China

2. School of Artificial Intelligence, Anhui Polytechnic University, Wuhu, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Opening Funding of National Key Laboratory of Electromagnetic Space Security, Laoshan Laboratory Science and Technology Innovation Project

Key Research and Development Projects in Anhui Province

Anhui Institute of Future Technology Enterprise Cooperation Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/27/4360151/10485614.pdf?arnumber=10485614

Cited by 1 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. Thickness Characterization of Steel Plate Coating Materials with Terahertz Time-Domain Reflection Spectroscopy Based on BP Neural Network;Sensors;2024-08-01

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