Machine learning-driven modeling of the effect of variable valve timing on fuel consumption and emission reduction in a turbocharged port-injection engine
This study presents a hybrid methodology integrating Design of Experiments and Machine Learning to model brake specific fuel consumption alongside HC and NO x emissions in a turbocharged gasoline engine, demonstrating that a desired calibration accuracy can be achieved using only 50% of the experimental data.
Faraz Javanshayani, AmirHossein Hamad, A. Parivar et al.
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