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Machine learning-driven modeling of the effect of variable valve timing on fuel consumption and emission reduction in a turbocharged port-injection engine

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TL;DR

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.

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