Quantitative structure?property relationships for auto-ignition temperatures of organic compounds

Auto Ignition ◽

ChemInform Abstract: Quantitative Structure-Property Relationships for the Prediction of Vapor Pressures of Organic Compounds from Molecular Structures.

ChemInform ◽

10.1002/chin.200042238 ◽

2000 ◽

Vol 31 (42) ◽

pp. no-no

Author(s):

Heidi Engelhardt McClelland ◽

Peter C. Jurs

Keyword(s):

Organic Compounds ◽

Molecular Structures ◽

Quantitative Structure ◽

Vapor Pressures ◽

Structure Property ◽

Optimisation of radial basis and backpropagation neural networks for modelling auto-ignition temperature by quantitative-structure property relationships

Chemometrics and Intelligent Laboratory Systems ◽

10.1016/0169-7439(95)00088-7 ◽

1996 ◽

Vol 32 (2) ◽

pp. 177-191 ◽

Cited By ~ 63

Author(s):

John Tetteh ◽

Edwin Metcalfe ◽

Sian L. Howells

Keyword(s):

Neural Networks ◽

Ignition Temperature ◽

Quantitative Structure ◽

Structure Property ◽

Backpropagation Neural Networks ◽

Auto Ignition ◽

Radial Basis ◽

Quantitative Structure−Property Relationships for the Prediction of Vapor Pressures of Organic Compounds from Molecular Structures

Journal of Chemical Information and Computer Sciences ◽

10.1021/ci990137c ◽

2000 ◽

Vol 40 (4) ◽

pp. 967-975 ◽

Cited By ~ 48

Author(s):

Heidi Engelhardt McClelland ◽

Peter C. Jurs

Keyword(s):

Organic Compounds ◽

Molecular Structures ◽

Quantitative Structure ◽

Vapor Pressures ◽

Structure Property ◽

Automatic formation method for structural descriptors of organic compounds for quantitative structure?property relationships

Russian Chemical Bulletin ◽

10.1007/bf00703684 ◽

1994 ◽

Vol 43 (8) ◽

pp. 1317-1319

Author(s):

M. I. Kumskov ◽

L. A. Ponomareva ◽

E. A. Smolenskii ◽

D. F. Mitushev ◽

N. S. Zefirov

Keyword(s):

Organic Compounds ◽

Quantitative Structure ◽

Structure Property ◽

Structural Descriptors ◽

Quantitative Structure Property Relationships ◽

Formation Method ◽

Automatic Formation

A Fuzzy ARTMAP Based on Quantitative Structure−Property Relationships (QSPRs) for Predicting Aqueous Solubility of Organic Compounds

Journal of Chemical Information and Computer Sciences ◽

10.1021/ci010323u ◽

2001 ◽

Vol 41 (5) ◽

pp. 1177-1207 ◽

Cited By ~ 45

Author(s):

Denise Yaffe ◽

Yoram Cohen ◽

Gabriela Espinosa ◽

Alex Arenas ◽

Francesc Giralt

Keyword(s):

Organic Compounds ◽

Aqueous Solubility ◽

Fuzzy Artmap ◽

Quantitative Structure ◽

Structure Property ◽

ChemInform Abstract: A Fuzzy ARTMAP Based on Quantitative Structure-Property Relationships (QSPRs) for Predicting Aqueous Solubility of Organic Compounds.

ChemInform ◽

10.1002/chin.200148223 ◽

2010 ◽

Vol 32 (48) ◽

pp. no-no

Author(s):

Denise Yaffe ◽

Yoram Cohen ◽

Gariela Espinosa ◽

Alex Arenas ◽

Francesc Giralt

Keyword(s):

Organic Compounds ◽

Aqueous Solubility ◽

Fuzzy Artmap ◽

Quantitative Structure ◽

Structure Property ◽

Dehalogenation of persistent halogenated organic compounds: A review of computational studies and quantitative structure–property relationships

Chemosphere ◽

10.1016/j.chemosphere.2015.02.013 ◽

2015 ◽

Vol 131 ◽

pp. 17-33 ◽

Cited By ~ 22

Author(s):

Jin Luo ◽

Jiwei Hu ◽

Xionghui Wei ◽

Liya Fu ◽

Lingyun Li

Keyword(s):

Organic Compounds ◽

Computational Studies ◽

Quantitative Structure ◽

Structure Property ◽

Halogenated Organic Compounds ◽

Fuzzy ARTMAP and Back-Propagation Neural Networks Based Quantitative Structure−Property Relationships (QSPRs) for Octanol−Water Partition Coefficient of Organic Compounds

Journal of Chemical Information and Computer Sciences ◽

10.1021/ci0103267 ◽

2002 ◽

Vol 42 (2) ◽

pp. 162-183 ◽

Cited By ~ 32

Author(s):

Denise Yaffe ◽

Yoram Cohen ◽

Gabriela Espinosa ◽

Alex Arenas ◽

Francesc Giralt

Keyword(s):

Neural Networks ◽

Partition Coefficient ◽

Organic Compounds ◽

Back Propagation ◽

Fuzzy Artmap ◽

Quantitative Structure ◽

Structure Property ◽

Water Partition Coefficient ◽

The Quantitative Structure-Property Relationships for the gas-ionic liquid partition coefficient of a large variety of organic compounds in three ionic liquids

Journal of Molecular Liquids ◽

10.1016/j.molliq.2021.117573 ◽

2021 ◽

pp. 117573

Author(s):

Karl Marti Toots ◽

Sulev Sild ◽

Jaan Leis ◽

William E. Acree ◽

Uko Maran

Keyword(s):

Ionic Liquid ◽

Ionic Liquids ◽

Partition Coefficient ◽

Organic Compounds ◽

Quantitative Structure ◽

Structure Property ◽

Quantitative structure-property relationships of retention indices of some sulfur organic compounds using random forest technique as a variable selection and modeling method

Journal of Separation Science ◽

10.1002/jssc.201600358 ◽

2016 ◽

Vol 39 (19) ◽

pp. 3835-3842

Author(s):

Nasser Goudarzi ◽

Davood Shahsavani ◽

Fereshteh Emadi-Gandaghi ◽

Mansour Arab Chamjangali

Keyword(s):

Random Forest ◽

Variable Selection ◽

Organic Compounds ◽

Retention Indices ◽

Modeling Method ◽

Quantitative Structure ◽

Structure Property ◽