title: Esters flash point prediction using artificial neural networks.
abstract: In this article, an artificial neural network to predict the flash point of 95 esters was implemented. Four variables were used for its development. A neural network with 4-5-8-5-1 topology was encountered to gain the best agreement of the experimental results with those predicted (square correlation coefficient (R(2)) and root mean square error were 0.99 and 5.46 K for the training phase and 0.96 and 13.02 K for the testing set).
authors.affiliation: Department of Physical Chemistry, Faculty of Sciences, University of Vigo, 32004 Ourense, Spain.
authors.forename: Gonzalo
authors.initials: G
authors.lastname: Astray
authors.forename: Juan F
authors.initials: JF
authors.lastname: Gálvez
authors.forename: Juan C
authors.initials: JC
authors.lastname: Mejuto
authors.forename: Oscar A
authors.initials: OA
authors.lastname: Moldes
authors.forename: Iago
authors.initials: I
authors.lastname: Montoya
mesh_terms: D004952:Esters / Q000737:chemistry*; D016571:Neural Networks, Computer
chemical_list: D004952:Esters