Development of Convolutional Neural Network-Based Models for Efficient and Reliable Flashpoint Prediction

The initial step in quantitative structure–property relationship (QSPR) modeling typically involves selecting relevant descriptors for predicting flammability characteristics. However, traditional selection methods face challenges and inefficiencies when dealing with large pools of molecular descrip...

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Bibliographic Details
Main Author:	Jiaxing Zhu (3930050) (author)
Other Authors:	Lin Hao (1597876) (author), Hao Zhang (15339) (author), Hongyuan Wei (1493320) (author)
Published:	2025
Subjects:	Genetics Computational Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified test data set reliable flashpoint prediction proposed approach leads predicting flammability characteristics convolutional neural network valid molecular descriptors 2 </ sup molecular descriptors r </ >< sup study proposes robust performance results demonstrate pure compounds large pools initial step fold cross cnn models bayesian optimization based models
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Development of Convolutional Neural Network-Based Models for Efficient and Reliable Flashpoint Prediction

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