Ensemble machine learning techniques for particulate emissions estimation from a highly boosted GDI engine fuelled by different gasoline blends
Light-duty vehicle emissions regulations worldwide impose stringent limits on particulate matter (PM) emissions, necessitating accurate modelling and prediction of particulate emissions across a range of sizes (as low as 10 nm). It has been shown that the decision tree-based ensemble machine learnin...
| Главные авторы: | , , , , , |
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| Формат: | Conference item |
| Язык: | English |
| Опубликовано: |
SAE International
2024
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