Neural Network Correction of PM3-Predicted Infrared Spectra

Barden, Christopher; Boysworth, Marc K.; Palocsay, Frank A.

doi:10.1021/ci970293o

Cited by 2 publications

(1 citation statement)

References 17 publications

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“…The information contained in the IR 99,108 and NMR spectra 22, 24, 44, 109 ± 112 as well as chromatographic retention indices 37,102,103,113 is closely related to the structures of organic molecules. In the studies cited in Table 1, the neural network algorithm for processing of such information was successfully used for the solution of miscellaneous practical problems related to the search for relationships between molecular structures and spectral properties, classification and forecasting of structural data and refinement of molecular structures on the basis of spectral information.…”

Section: Comparison Of a Neural Network Algorithm With Standard Stati...mentioning

confidence: 99%

Neural networks as a method for elucidating structure–property relationships for organic compounds

Halberstam¹,

Baskin²,

Palyulin³

et al. 2003

Russ. Chem. Rev.

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The published data devoted to the use of the neural The published data devoted to the use of the neural network approach in the simulation of structure ± property rela-network approach in the simulation of structure ± property relationships for organic compounds are reviewed. The basic princi-tionships for organic compounds are reviewed. The basic principles of the neural network simulation are discussed along with the ples of the neural network simulation are discussed along with the characteristic features of the neural network approach typical of characteristic features of the neural network approach typical of the representation and classification of structural chemical data. the representation and classification of structural chemical data. Brief information on neural network models of spectral character-Brief information on neural network models of spectral characteristics, reactivities, physicochemical properties and biological istics, reactivities, physicochemical properties and biological activities of organic compounds is presented. The bibliography activities of organic compounds is presented. The bibliography includes 159 references includes 159 references. . Neural networks consist, as a rule, of a set of relatively simple computing elements termed neurons; the latter are arranged in several layers and are linked to one another by numerous connections. The layers are usually subdivided into three groups, viz., input, hidden and output (Fig. 1). Each connection between two neurons is defined by a real number termed connection

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