Opportunity to Improve Diesel-Fuel Cetane-Number Prediction from Easily Available Physical Properties and Application of the Least-Squares Method and Artificial Neural Networks

A database of 140 diesel fuels having cetane numbers in the range of 10–70 points; densities at 15 °C; and distillation characteristics according to ASTM D-86 T 10%, T 50%, and T 90% was used to develop new procedures for predicting diesel cetane numbers by application of the least-squares method (L...

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Veröffentlicht in:	Energy & fuels 2015-03, Vol.29 (3), p.1520-1533
Hauptverfasser:	Stratiev, Dicho, Marinov, Ivaylo, Dinkov, Rosen, Shishkova, Ivelina, Velkov, Ilian, Sharafutdinov, Ilshat, Nenov, Svetoslav, Tsvetkov, Tsvetelin, Sotirov, Sotir, Mitkova, Magdalena, Rudnev, Nikolay
Format:	Artikel
Sprache:	eng
Schlagworte:	Cetane number Diesel fuels Distillates Learning theory Mathematical models Matlab Neural networks
Online-Zugang:	Volltext
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