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Application of the Artificial Neural Networks and Fuzzy Logic for the Prediction of Reactivity of Molecules in Radical Reactions

  • V. E. TumanovEmail author
Chapter
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 307)

Abstract

This paper discusses the use of feed-forward artificial neural network to predict the reactivity of organic molecules in the bimolecular radical reactions in the liquid phase and the use of the fuzzy knowledge base to identify the empirical dependence of the activation energy of reactions phenyl radical (C6Hº 5, 4-CH3–C6Hº 5, 4-Br–C6Hº 5, 4-Cl–C6Hº 5 etc.) with hydrocarbons in the liquid phase from thermochemical data. Also artificial neural network was used to predict the values of C–H bonds dissociation energies of hydrocarbons on experimental data of radical reactions Rº + RH.

Keywords

Feed-forward artificial neural network Subject-oriented science intelligence system Reactivity of organic molecules Radical reaction Fuzzy knowledge base Rate constant Activation energy Bond dissociation energy 

References

  1. 1.
    Gasteiger J, Zupan J (1993) Neural networks in chemistry,” Angev. Chem. Int. Ed. Engl. 32:503–527Google Scholar
  2. 2.
    Tumanov V, Gaifullin G (2012) Subject-oriented science intelligent system on physical chemistry of radical reactions”, Modern Advances in Intelligent Systems and Tools 431:121–126Google Scholar
  3. 3.
    Mallard WG, Westley F, Herron JT, Hampson RF (1994) NIST Chemical Kinetics Database – Ver. 6.0. NIST Standard Reference Data, Gaithersburg, MD.Google Scholar
  4. 4.
    Semenov NN (1935) Chemical Kinetics and Chain Reactions. London, Oxford Univ. pressGoogle Scholar
  5. 5.
    Denisov ET (1997) New empirical models of free radical abstraction reactions. Uspekhi Khimii 66:953–971Google Scholar
  6. 6.
    Denisov ET, Tumanov VE (1994) Transition-State Model as the Result of 2 Morse Terms Crossing Applied to Atomic-Hydrogen Reactions. Zhurnal Fizicheskoi Khimii 68:719–725Google Scholar
  7. 7.
    Lill JH (2011) Fuzzy Control and Identification. John Wiley & Sons, IncorporatedGoogle Scholar
  8. 8.
    Luo YR (2003) HandOther of Bond Dissociation Energies in Organic Compounds. CRC Press, Boca Raton, FLGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Laboratory of Information Support for ResearchInstitute of Problems of Chemical Physics RASChernogolovkaRussian Federation

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