Simple Alternative to Neural Networks for Predicting Sublimation Enthalpies from Fragment Contributions
2012
Mathieu, D. (Didier)
Taking advantage of an extended data set of sublimation enthalpies recently used to develop an artificial neural network for the prediction of this property, an alternative model based on 35 atom and ring contributions is presently reported. The values predicted using both approaches are remarkably similar, although the present one is much simpler and less empirical.
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