Comparison of Genetic Algorithm Based Support Vector Machine and Genetic Algorithm Based RBF Neural Network in Quantitative Structure-Property Relationship Models on Aqueous Solubility of Polycyclic Aromatic Hydrocarbons

Quantitative structure-property relationship (QSPR) study to predict retention time of polycyclic aromatic hydrocarbons using the random forest and artificial neural network methods

Structural Chemistry ◽

10.1007/s11224-019-01476-w ◽

2020 ◽

Vol 31 (4) ◽

pp. 1281-1288

Author(s):

Moona Emrarian ◽

Mahmoud Reza Sohrabi ◽

Nasser Goudarzi ◽

Fariba Tadayon

Keyword(s):

Neural Network ◽

Aromatic Hydrocarbons ◽

Quantitative Structure ◽

Structure Property ◽

Network Methods ◽

Polycyclic Aromatic ◽

Qspr Study

Quantitative structure–property relationship models to predict thermodynamic properties of some mono and polycyclic aromatic hydrocarbons using genetic algorithm‐multiple linear regression

Journal of the Chinese Chemical Society ◽

10.1002/jccs.201900319 ◽

2019 ◽

Vol 67 (6) ◽

pp. 969-982

Author(s):

Fatemeh Dialamehpour ◽

Fatemeh Shafiei

Keyword(s):

Genetic Algorithm ◽

Linear Regression ◽

Thermodynamic Properties ◽

Multiple Linear Regression ◽

Aromatic Hydrocarbons ◽

Quantitative Structure ◽

Structure Property ◽

Quantitative structure–property relationship studies of gas-to-wet butyl acetate partition coefficient of some organic compounds using genetic algorithm and artificial neural network

Structural Chemistry ◽

10.1007/s11224-010-9669-8 ◽

2010 ◽

Vol 21 (6) ◽

pp. 1241-1252 ◽

Cited By ~ 20

Author(s):

Hassan Golmohammadi ◽

Zahra Dashtbozorgi

Keyword(s):

Neural Network ◽

Genetic Algorithm ◽

Partition Coefficient ◽

Organic Compounds ◽

Butyl Acetate ◽

Quantitative Structure ◽

Structure Property ◽

Structure Property Relationship

Quantitative Structure-Property Relationship: XXII. Polycyclic Aromatic Hydrocarbons

Russian Journal of General Chemistry ◽

10.1007/s11176-005-0511-8 ◽

2005 ◽

Vol 75 (11) ◽

pp. 1790-1794

Author(s):

I. B. Golovanov ◽

S. M. Zhenodarova

Keyword(s):

Aromatic Hydrocarbons ◽

Quantitative Structure ◽

Structure Property ◽

Property Relationship ◽

Prediction of solubility for polycyclic aromatic hydrocarbons in supercritical carbon dioxide using wavelet neural networks in quantitative structure property relationship

The Journal of Supercritical Fluids ◽

10.1016/j.supflu.2004.02.003 ◽

2004 ◽

Vol 32 (1-3) ◽

pp. 73-78 ◽

Cited By ~ 29

Author(s):

T. Khayamian ◽

M. Esteki

Keyword(s):

Carbon Dioxide ◽

Neural Networks ◽

Supercritical Carbon Dioxide ◽

Aromatic Hydrocarbons ◽

Quantitative Structure ◽

Structure Property ◽

Wavelet Neural Networks ◽

Quantitative structure–property relationship studies on direct photolysis of selected polycyclic aromatic hydrocarbons in atmospheric aerosol

Chemosphere ◽

10.1016/s0045-6535(00)00077-1 ◽

2001 ◽

Vol 42 (3) ◽

pp. 263-270 ◽

Cited By ~ 36

Author(s):

Jingwen Chen ◽

Xie Quan ◽

Yun Yan ◽

Fenglin Yang ◽

W.J.G.M Peijnenburg

Keyword(s):

Aromatic Hydrocarbons ◽

Atmospheric Aerosol ◽

Quantitative Structure ◽

Structure Property ◽

Direct Photolysis ◽

Property Relationship ◽

Comparison of multiple linear regression, partial least squares and artificial neural network for quantitative structure retention relationships of some polycyclic aromatic hydrocarbons

Analytical Methods ◽

10.1039/c2ay25711d ◽

2012 ◽

Vol 4 (10) ◽

pp. 3381 ◽

Cited By ~ 6

Author(s):

Mohamad Mahani ◽

Homa ShaikhGhomi

Keyword(s):

Neural Network ◽

Linear Regression ◽

Multiple Linear Regression ◽

Least Squares ◽

Aromatic Hydrocarbons ◽

Quantitative Structure ◽

Polycyclic Aromatic ◽

Structure Retention

Quantitative structure/property relationship analysis of Caco‐2 permeability using a genetic algorithm‐based partial least squares method

Journal of Pharmaceutical Sciences ◽

10.1002/jps.10214 ◽

2002 ◽

Vol 91 (10) ◽

pp. 2230-2239 ◽

Cited By ~ 40

Author(s):

Fumiyoshi Yamashita ◽

Suchada Wanchana ◽

Mitsuru Hashida

Keyword(s):

Genetic Algorithm ◽

Least Squares ◽

Partial Least Squares ◽

Least Squares Method ◽

Quantitative Structure ◽

Structure Property ◽

Relationship Analysis ◽

Partial Least Squares Method

Quantitative structure-property relationship modeling of water-to-wet butyl acetate partition coefficient of 76 organic solutes using multiple linear regression and artificial neural network

Journal of Separation Science ◽

10.1002/jssc.201000448 ◽

2010 ◽

Vol 33 (23-24) ◽

pp. 3800-3810 ◽

Cited By ~ 11

Author(s):

Zahra Dashtbozorgi ◽

Hassan Golmohammadi

Keyword(s):

Neural Network ◽

Linear Regression ◽

Partition Coefficient ◽

Multiple Linear Regression ◽

Butyl Acetate ◽

Organic Solutes ◽

Quantitative Structure ◽

Structure Property ◽

Structure Property Relationship

Aqueous solubility of poorly water-soluble drugs: Prediction using similarity and quantitative structure-property relationship models

Korean Journal of Chemical Engineering ◽

10.1007/s11814-008-0143-x ◽

2008 ◽

Vol 25 (4) ◽

pp. 865-873 ◽

Cited By ~ 5

Author(s):

Junhyoung Kim ◽

Dong Hyun Jung ◽

Hokyoung Rhee ◽

Seung-Hoon Choi ◽

Min Jae Sung ◽

...

Keyword(s):

Aqueous Solubility ◽

Water Soluble ◽

Quantitative Structure ◽

Structure Property ◽

Poorly Water Soluble Drugs ◽

Property Relationship ◽

Water Soluble Drugs ◽

Poorly Water Soluble