Neural network-graph theory approach to the prediction of the physical properties of organic compounds

Gakh, A A; Gakh, E G; Sumpter, B G; Noid, D W

doi:10.1021/ci00020a017

Title: Neural network-graph theory approach to the prediction of the physical properties of organic compounds

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Abstract

A new computational scheme is developed to predict physical properties of organic compounds on the basis of their molecular structure. The method uses graph theory to encode the structural information which is the numerical input for a neutral network. Calculated results for a series of saturated hydrocarbons demonstrate average accuracies of 1--2% with maximum deviations of 12--14%.

Authors:

Gakh, A A; Gakh, E G; Sumpter, B G; Noid, D W ^[1]

Oak Ridge National Lab., TN (United States). Chemistry Div.

Publication Date:: Sat Dec 31 00:00:00 EST 1994

Sponsoring Org.:: USDOE

OSTI Identifier:: 131610

DOE Contract Number:: AC05-84OR21400

Resource Type:: Journal Article

Journal Name:: Journal of Chemical Information and Computer Sciences

Additional Journal Information:: Journal Volume: 34; Journal Issue: 4; Other Information: PBD: 1994

Country of Publication:: United States

Language:: English

Subject:: 02 PETROLEUM; 40 CHEMISTRY; 99 MATHEMATICS, COMPUTERS, INFORMATION SCIENCE, MANAGEMENT, LAW, MISCELLANEOUS; HYDROCARBONS; PHYSICAL PROPERTIES; ORGANIC COMPOUNDS; NEURAL NETWORKS; MOLECULAR STRUCTURE; ALGORITHMS; COMPUTER ARCHITECTURE; CALCULATION METHODS; THEORETICAL DATA

Citation Formats


                    Gakh, A A, Gakh, E G, Sumpter, B G, and Noid, D W. Neural network-graph theory approach to the prediction of the physical properties of organic compounds.  United States: N. p., 1994. 
        Web.  doi:10.1021/ci00020a017.

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                    Gakh, A A, Gakh, E G, Sumpter, B G, & Noid, D W. Neural network-graph theory approach to the prediction of the physical properties of organic compounds.  United States.  https://doi.org/10.1021/ci00020a017

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                    Gakh, A A, Gakh, E G, Sumpter, B G, and Noid, D W. 1994.  
        "Neural network-graph theory approach to the prediction of the physical properties of organic compounds".  United States.  https://doi.org/10.1021/ci00020a017.

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@article{osti_131610,

  title        = {Neural network-graph theory approach to the prediction of the physical properties of organic compounds},

  author       = {Gakh, A A and Gakh, E G and Sumpter, B G and Noid, D W},

  abstractNote = {A new computational scheme is developed to predict physical properties of organic compounds on the basis of their molecular structure. The method uses graph theory to encode the structural information which is the numerical input for a neutral network. Calculated results for a series of saturated hydrocarbons demonstrate average accuracies of 1--2% with maximum deviations of 12--14%.},

  doi          = {10.1021/ci00020a017},

  url          = {https://www.osti.gov/biblio/131610},
  journal      = {Journal of Chemical Information and Computer Sciences},
number       = 4,

  volume       = 34,

  place        = {United States},

  year         = {Sat Dec 31 00:00:00 EST 1994},

  month        = {Sat Dec 31 00:00:00 EST 1994}

}

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