Flash point and cetane number predictions for fuel compounds using quantitative structure property relationship (QSPR) methods

Energy and Fuels

Volumn 25, Issue 9, 2011, Pages 3900-3908

  Saldana, Diego Alonso ^a   Starck, Laurie ^a   Mougin, Pascal ^a   Rousseau, Bernard ^b   Pidol, Ludivine ^a   Jeuland, Nicolas ^a   Creton, Benoit ^a  

^a IFP ENERGIES NOUVELLES   (France)

^b UNIVERSITÉ PARIS SUD   (France)

Author keywords

[No Author keywords available]

Indexed keywords

CARBON ATOMS; DESCRIPTORS; EXPERIMENTAL DATA; FEED-FORWARD ARTIFICIAL NEURAL NETWORKS; FLASH POINTS; FUEL PROPERTIES; FUNCTION APPROXIMATION; GENERAL REGRESSION NEURAL NETWORK; GRAPH MACHINE; INDIVIDUAL MODELS; MOLECULAR DESCRIPTORS; NON-LINEAR MODEL; PARTIAL LEAST SQUARES; PREDICTIVE MODELS; QSPR MODEL; QUANTITATIVE STRUCTURE PROPERTY RELATIONSHIPS;

ANTIKNOCK RATING; DIESEL FUELS; FORECASTING; FUELS; FUNCTIONAL GROUPS; HYDROCARBONS; LEAST SQUARES APPROXIMATIONS;

NEURAL NETWORKS;

EID: 80052871511     PISSN: 08870624     EISSN: 15205029     Source Type: Journal    
DOI: 10.1021/ef200795j     Document Type: Article

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