Prediction of the Electrical Strength and Boiling Temperature of the Substitutes for Greenhouse Gas SF₆ Using Neural Network and Random Forest

Prediction of the Electrical Strength and Boiling Temperature of the Substitutes for Greenhouse Gas SF₆ Using Neural Network and Random Forest

Finding substitutes for sulfur hexafluoride (SF<sub>6</sub>), a gas with extremely high global warming potential, has been a persistent effort for years in the field of high voltage power equipment, which focuses on the evaluation of the electrical strength and boiling temperature for th...

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Bibliographic Details
Main Authors: Hao Sun, Luqi Liang, Chunlin Wang, Yi Wu, Fei Yang, Mingzhe Rong
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
SF₆ substitutes
artificial neural network
random forest
electrical strength
boiling temperature
Online Access:https://ieeexplore.ieee.org/document/9123755/

Internet

https://ieeexplore.ieee.org/document/9123755/

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