Neural network-based prediction of auto-ignition temperature of ternary mixed liquids

Neural network-based prediction of auto-ignition temperature of ternary mixed liquids

Auto-ignition temperature (AIT) is one of the crucial exponents in the design of fire and explosion safety measures. Therefore, in this study, quantitative structure-property relationship approach was used to predict the AIT of ternary hybrid liquids based on molecular structure information. The opt...

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Bibliographic Details
Main Authors: Bingyu Guo, Zehui Cheng, Shuangqi Hu
Format: Article
Language:English
Published: Elsevier 2024-04-01
Series:Heliyon
Subjects:
Auto-ignition temperature
Quantitative structure-property relationship
Anti-propagation neural networks
One-dimensional convolutional neural network
Ternary mixed liquid
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844024047443

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http://www.sciencedirect.com/science/article/pii/S2405844024047443

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