@ARTICLE{Bąkowski_Andrzej_Vibroacoustic_2018, author={Bąkowski, Andrzej and Kekez, Michał and Radziszewski, Leszek and Sapietova, Alžbeta}, volume={vol. 43}, number={No 3}, journal={Archives of Acoustics}, pages={385-395}, howpublished={online}, year={2018}, publisher={Polish Academy of Sciences, Institute of Fundamental Technological Research, Committee on Acoustics}, abstract={Five models and methodology are discussed in this paper for constructing classifiers capable of recognizing in real time the type of fuel injected into a diesel engine cylinder to accuracy acceptable in practical technical applications. Experimental research was carried out on the dynamic engine test facility. The signal of in-cylinder and in-injection line pressure in an internal combustion engine powered by mineral fuel, biodiesel or blends of these two fuel types was evaluated using the vibro-acoustic method. Computational intelligence methods such as classification trees, particle swarm optimization and random forest were applied.}, type={Artykuły / Articles}, title={Vibroacoustic Real Time Fuel Classification in Diesel Engine}, URL={http://journals.pan.pl/Content/108110/PDF/123910.pdf}, doi={10.24425/123910}, keywords={fuel recognition, classification trees, particle swarm optimization, random forest}, }