Prediction of Flash Point of Materials Using Bayesian Kernel Machine Regression Based on Gaussian Processes With LASSO‐Like Spike‐and‐Slab Hyperprior

ABSTRACT The determination of flash points is a critical aspect of chemical safety, essential for assessing explosion hazards and fire risks associated with flammable solutions. With the advent of new chemical blends and the increasing complexity of chemical waste management, the need for accurate a...

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Veröffentlicht in:	Journal of chemometrics 2024-10, Vol.38 (10), p.n/a
Hauptverfasser:	Jeong, Keunhong, Hyun Nam, Ji, Lee, Seul, Koo, Jahyun, Lee, Jooyeon, Yu, Donghyun, Jo, Seongil, Kim, Jaeoh
Format:	Artikel
Sprache:	eng
Schlagworte:	Bayesian analysis Bayesian kernel machine Chemical wastes Fire hazards Flammability Flash point Gaussian process Hazard assessment Kernel functions LASSO‐like spike‐and‐slab prior prediction Prediction models Predictions Regression models Safety analysis Safety management Support vector machines Uncertainty analysis Waste management
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