PDFAbstract: 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.
Keywords: fuzzy neural network, Takagi-Sugeno-Kang model, bond dissociation energy, halogenated hydrocarbon, electronegativity, bond force constant, halogen atom size
Cite this paper
Vladimir E. Tumanov, Elena S. Amosova, Bulat N. Gaifullin, Andrey I. Prokhorov. (2016) 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, 1 , 146-148
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