Deep learning algorithms for assessing sustainable jet fuels from two-dimensional gas chromatography

Keyphrases

• Jet Fuel 100%
• Deep Learning Algorithm 100%
• Two-dimensional Gas Chromatography 100%
• GC×GC 100%
• Sustainable Aviation Fuel 40%
• Neural Network 20%
• Physicochemical Properties 20%
• Learning-based 20%
• Blending Ratio 20%
• Aromatics 20%
• Dataset Size 20%
• Detection Scheme 20%
• Petroleum-based 20%
• Small Dataset 20%
• Artificial Neural Network 20%
• Over 80 20%
• Novel Chemicals 20%
• Chemical Characteristics 20%
• Clustering Property 20%
• Source Method 20%
• Distillation 20%
• Partial Least Squares Regression Model 20%
• Kinematic Viscosity 20%
• Carbon number 20%
• Optimal Clustering 20%
• Novelty Detection 20%
• Paraffin 20%
• Predictive Error 20%
• Latent Representation 20%
• Aviation Fuel 20%
• Hydrocarbon Groups 20%
• Isoparaffin 20%
• Wide Neural Network 20%
• Comprehensive Two-dimensional Gas Chromatography 20%
• Auto-encoding Neural Network 20%
• Reference Fuels 20%
• Fuel Properties Assessment 20%
• Novelty Score 20%

Chemical Engineering

• Neural Network 100%
• Deep Learning 100%
• Two Dimensional Gas Chromatography 100%