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Experimental investigation and prediction of performance and emission responses of a CI engine fuelled with different metal-oxide based nanoparticles–diesel blends using different machine learning algorithms
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Ü. Ağbulut Et Al. , "Experimental investigation and prediction of performance and emission responses of a CI engine fuelled with different metal-oxide based nanoparticles–diesel blends using different machine learning algorithms," Energy , vol.215, 2021

Ağbulut, Ü. Et Al. 2021. Experimental investigation and prediction of performance and emission responses of a CI engine fuelled with different metal-oxide based nanoparticles–diesel blends using different machine learning algorithms. Energy , vol.215 .

Ağbulut, Ü., Gürel, A. E., & Sarıdemir, S., (2021). Experimental investigation and prediction of performance and emission responses of a CI engine fuelled with different metal-oxide based nanoparticles–diesel blends using different machine learning algorithms. Energy , vol.215.

Ağbulut, Ümit, Ali Etem Gürel, And Suat Sarıdemir. "Experimental investigation and prediction of performance and emission responses of a CI engine fuelled with different metal-oxide based nanoparticles–diesel blends using different machine learning algorithms," Energy , vol.215, 2021

Ağbulut, Ümit Et Al. "Experimental investigation and prediction of performance and emission responses of a CI engine fuelled with different metal-oxide based nanoparticles–diesel blends using different machine learning algorithms." Energy , vol.215, 2021

Ağbulut, Ü. Gürel, A. E. And Sarıdemir, S. (2021) . "Experimental investigation and prediction of performance and emission responses of a CI engine fuelled with different metal-oxide based nanoparticles–diesel blends using different machine learning algorithms." Energy , vol.215.

@article{article, author={Ümit AĞBULUT Et Al. }, title={Experimental investigation and prediction of performance and emission responses of a CI engine fuelled with different metal-oxide based nanoparticles–diesel blends using different machine learning algorithms}, journal={Energy}, year=2021}