Tetteh, J.; Suzuki, T.; Metcalfe, E.; Howells, S. Quantitative Structure-Property Relationships for the Estimation of Boiling Point and Flash Point Using a Radial Basis Function Neural Network. J. Chem. Inf. Model. 1999, 39, 491-507.

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Tetteh, J.; Suzuki, T.; Metcalfe, E.; Howells, S. Quantitative Structure-Property Relationships for the Estimation of Boiling Point and Flash Point Using a Radial Basis Function Neural Network. J. Chem. Inf. Model. 1999, 39, 491-507.

QDB archive DOI: 10.15152/QDB.158   DOWNLOAD

QsarDB content

Property Tb: Boiling point [°C]

Tab7_Tb: RBF-NN model for diverse chemicals i

Neural network (regression)

Open in:QDB ExplorerQDB Predictor

NameTypen

R2

σ

Training settraining1350.97312.754
Validation setexternal validation1330.95715.683
Testing setexternal validation1320.91521.674

Property Tf: Flash point [°C]

Tab7_Tf: RBF-NN model for diverse chemicals i

Neural network (regression)

Open in:QDB ExplorerQDB Predictor

NameTypen

R2

σ

Training settraining1350.9639.879
Validation setexternal validation1330.92814.100
Testing setexternal validation1320.92213.964

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When using this QDB archive, please cite (see details) it together with the original article:

  • Ahte, P. Data for: Quantitative Structure-Property Relationships for the Estimation of Boiling Point and Flash Point Using a Radial Basis Function Neural Network. QsarDB repository, QDB.158. 2015. http://dx.doi.org/10.15152/QDB.158

  • Tetteh, J.; Suzuki, T.; Metcalfe, E.; Howells, S. Quantitative Structure-Property Relationships for the Estimation of Boiling Point and Flash Point Using a Radial Basis Function Neural Network. J. Chem. Inf. Model. 1999, 39, 491-507. http://dx.doi.org/10.1021/ci980026y

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dc.date.accessioned2015-05-28T20:07:11Z
dc.date.available2015-05-28T20:07:11Z
dc.date.issued2015-05-28
dc.identifier.urihttp://hdl.handle.net/10967/158
dc.identifier.urihttp://dx.doi.org/10.15152/QDB.158
dc.description.abstractRadial basis function (RBF) neural network models for the simultaneous estimation of flash point (Tf) and boiling point (Tb) based on 25 molecular functional groups and their first-order molecular connectivity index (1χ) have been developed. The success of the whole modeling process depended on a network optimization strategy based on biharmonic spline interpolation for the selection of an optimum RBF neurons (n) in the hidden layer and their associated spread parameter (σ). The RBF networks were trained by the Orthogonal Least Squares (OLS) learning algorithm. After dividing the total database of 400 compounds into training (134), validation (133), and testing (133), the average absolute errors obtained for the validation and testing sets ranges from 10 °C to 12 °C and 11 °C to14 °C for Tf and Tb, respectively, and are in agreement with the experimental value of about 10 °C. Results of a standard Partial Least Square (PLS) regression model for single output predictions range from 23 °C to 24 °C and 18 °C to 20 °C for Tf and Tb, respectively, indicating the superior predictive ability of the neural model and strongly suggests that a nonlinear relationship exists between the input and target parameters of the data. The robustness of the neural model was successfully examined by a random split cross validation based on pooling together of the validation and test data sets. The study shows that the simple numerical coding of a molecule based on its formula together with its 1χ is an attractive way of estimating the flammability properties of organic compounds via an RBF neural network
dc.publisherPriit Ahte
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleTetteh, J.; Suzuki, T.; Metcalfe, E.; Howells, S. Quantitative Structure-Property Relationships for the Estimation of Boiling Point and Flash Point Using a Radial Basis Function Neural Network. J. Chem. Inf. Model. 1999, 39, 491-507.
qdb.property.endpoint1. Physical Chemical Properties 1.2. Boiling pointen_US
qdb.property.endpoint1. Physical Chemical Properties 1.19. Flash pointen_US
qdb.descriptor.applicationGRAPH IIIen_US
qdb.prediction.applicationMATLABen_US
bibtex.entryarticleen_US
bibtex.entry.authorTetteh, J.
bibtex.entry.authorSuzuki, T.
bibtex.entry.authorMetcalfe, E.
bibtex.entry.authorHowells, S.
bibtex.entry.doi10.1021/ci980026yen_US
bibtex.entry.journalJ. Chem. Inf. Model.en_US
bibtex.entry.monthMay
bibtex.entry.number3en_US
bibtex.entry.pages491-507en_US
bibtex.entry.titleQuantitative Structure-Property Relationships for the Estimation of Boiling Point and Flash Point Using a Radial Basis Function Neural Networken_US
bibtex.entry.volume39en_US
bibtex.entry.year1999
qdb.model.typeNeural network (regression)en_US


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