В журнале International Journal of Mathematical and Computational Methods. 2016. Vol. 1. P. 146-148 опубликована статья написанная с участием наших авторов.
Tumanov V.E., Amosova E.S., Gaifullin B.N., Prokhorov A.I. Using fuzzy artificial neural network TSK (Takagi, Sugeno, Kang) for approximation and prediction of dissociation energy of C-X-bonds (X=F, Cl, Br, I) in halogenated hydrocarbons // International Journal of Mathematical and Computational Methods. 2016. Vol. 1. P. 146-148.
Abstract: The Takagi-Sugeno-Kang (TSK) fuzzy artificial neural network has been used for approximation of
dissociation energies of C-X-bonds (X=F, Cl, Br, I) in halogenated hydrocarbons by the experimental data.
Characteristics of molecule: electronegativity, force constant of the bond, the atom size of halogen served as
variables. The comparison of predictions by the developed fuzzy network with the experimental data on the test
sample is given. The obtained results are in good agreement with the experimental data.
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