A Combined Semiempirical MO/Neural Net Technique for Estimating 13C Chemical Shifts
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A back-propagation artificial neural net has been trained to estimate 13C chemical shifts from the results of AM1 and PM3 semiempirical MO calculations. The input descriptors include the atom-centered monopole, dipole and quadrupole moments derived from the natural atomic orbital/point charge (NAO/PC) model, the four highest bond orders to the carbon atom being considered and the elements to which these bonds are made. The resulting net estimates the chemical shifts of a test set of 156 chemical shifts with a standard deviation of less than 7 ppm from the experimental values for AM1 and slightly more for PM3.
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