Fluorescence optosensor using an artificial neural network for screening of polycyclic aromatic hydrocarbons

J.F. Fernández-Sánchez; A. Segura Carretero; J.M. Benı́tez-Sánchez; C. Cruces-Blanco; A. Fernández-Gutiérrez

doi:10.1016/j.aca.2004.01.012

Fluorescence optosensor using an artificial neural network for screening of polycyclic aromatic hydrocarbons

Analytica Chimica Acta ◽

10.1016/j.aca.2004.01.012 ◽

2004 ◽

Vol 510 (2) ◽

pp. 183-187 ◽

Cited By ~ 8

Author(s):

J.F. Fernández-Sánchez ◽

A. Segura Carretero ◽

J.M. Benı́tez-Sánchez ◽

C. Cruces-Blanco ◽

A. Fernández-Gutiérrez

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Polycyclic Aromatic Hydrocarbons ◽

Aromatic Hydrocarbons ◽

Polycyclic Aromatic ◽

Artificial Neural

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Prediction of the Lee retention indices of polycyclic aromatic hydrocarbons by artificial neural network

Journal of Chromatography A ◽

10.1016/j.chroma.2006.01.080 ◽

2006 ◽

Vol 1108 (2) ◽

pp. 279-284 ◽

Cited By ~ 15

Author(s):

Biljana Škrbić ◽

Antonije Onjia

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Polycyclic Aromatic Hydrocarbons ◽

Aromatic Hydrocarbons ◽

Retention Indices ◽

Polycyclic Aromatic ◽

Artificial Neural

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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 ◽

Artificial Neural Network ◽

Polycyclic Aromatic Hydrocarbons ◽

Linear Regression ◽

Multiple Linear Regression ◽

Least Squares ◽

Aromatic Hydrocarbons ◽

Quantitative Structure ◽

Polycyclic Aromatic ◽

Structure Retention

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Interpretative optimization and artificial neural network modeling of the gas chromatographic separation of polycyclic aromatic hydrocarbons

Talanta ◽

10.1016/j.talanta.2008.02.004 ◽

2008 ◽

Vol 76 (1) ◽

pp. 66-71 ◽

Cited By ~ 10

Author(s):

Snežana Sremac ◽

Aleksandar Popović ◽

Žaklina Todorović ◽

Đuro Čokeša ◽

Antonije Onjia

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Polycyclic Aromatic Hydrocarbons ◽

Aromatic Hydrocarbons ◽

Chromatographic Separation ◽

Network Modeling ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling ◽

Polycyclic Aromatic ◽

Gas Chromatographic Separation

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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 ◽

Artificial Neural Network ◽

Polycyclic Aromatic Hydrocarbons ◽

Aromatic Hydrocarbons ◽

Quantitative Structure ◽

Structure Property ◽

Network Methods ◽

Structure Property Relationship ◽

Polycyclic Aromatic ◽

Qspr Study

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Effects of corn straw on dissipation of polycyclic aromatic hydrocarbons and potential application of backpropagation artificial neural network prediction model for PAHs bioremediation

Ecotoxicology and Environmental Safety ◽

10.1016/j.ecoenv.2019.109745 ◽

2019 ◽

Vol 186 ◽

pp. 109745 ◽

Cited By ~ 5

Author(s):

Huanyu Bao ◽

Jinfeng Wang ◽

Jiao Li ◽

He Zhang ◽

Fuyong Wu

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Polycyclic Aromatic Hydrocarbons ◽

Aromatic Hydrocarbons ◽

Potential Application ◽

Corn Straw ◽

Polycyclic Aromatic ◽

Neural Network Prediction ◽

Network Prediction ◽

Backpropagation Artificial Neural Network

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Retention time prediction of polycyclic aromatic hydrocarbons in gas chromatography–mass spectrometry using QSPR based on random forests and artificial neural network

Structural Chemistry ◽

10.1007/s11224-020-01614-9 ◽

2020 ◽

Vol 32 (1) ◽

pp. 49-61

Author(s):

Moona Emrarian ◽

Mahmoud Reza Sohrabi ◽

Nasser Goudarzi ◽

Fariba Tadayon

Keyword(s):

Neural Network ◽

Mass Spectrometry ◽

Artificial Neural Network ◽

Gas Chromatography ◽

Polycyclic Aromatic Hydrocarbons ◽

Random Forests ◽

Aromatic Hydrocarbons ◽

Gas Chromatography Mass Spectrometry ◽

Time Prediction ◽

Polycyclic Aromatic

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Detection of Polycyclic Aromatic Hydrocarbons Combining Fluorescence Analysis with ABC-BP Neural Network

Chinese Journal of Lasers ◽

10.3788/cjl201542.1115001 ◽

2015 ◽

Vol 42 (11) ◽

pp. 1115001

Author(s):

王书涛 Wang Shutao ◽

陈东营 Chen Dongying ◽

王兴龙 Wang Xinglong ◽

韩欢欢 Han Huanhuan ◽

王佳亮 Wang Jialiang

Keyword(s):

Neural Network ◽

Polycyclic Aromatic Hydrocarbons ◽

Aromatic Hydrocarbons ◽

Bp Neural Network ◽

Fluorescence Analysis ◽

Polycyclic Aromatic

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Artificial neural network predictions of polycyclic aromatic hydrocarbon formation in premixed n-heptane flames

Fuel Processing Technology ◽

10.1016/j.fuproc.2006.08.002 ◽

2006 ◽

Vol 87 (11) ◽

pp. 1031-1036 ◽

Cited By ~ 16

Author(s):

Fikret Inal

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Polycyclic Aromatic Hydrocarbon ◽

Aromatic Hydrocarbon ◽

Polycyclic Aromatic ◽

Hydrocarbon Formation ◽

Artificial Neural

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Artificial neural networks (ANNs) in the analysis of polycyclic aromatic hydrocarbons in water samples by synchronous fluorescence

Analytica Chimica Acta ◽

10.1016/s0003-2670(98)00778-8 ◽

1999 ◽

Vol 384 (3) ◽

pp. 261-269 ◽

Cited By ~ 17

Author(s):

R. Ferrer ◽

J. Guiteras ◽

J.L. Beltrán

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Polycyclic Aromatic Hydrocarbons ◽

Aromatic Hydrocarbons ◽

Water Samples ◽

Synchronous Fluorescence ◽

Polycyclic Aromatic ◽

Artificial Neural

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Use of a neural network for the analysis of fluorescence spectra from mixtures of polycyclic aromatic hydrocarbons

10.1117/12.56530 ◽

1992 ◽

Cited By ~ 2

Author(s):

John M. Andrews ◽

Stephen H. Lieberman

Keyword(s):

Neural Network ◽

Polycyclic Aromatic Hydrocarbons ◽

Aromatic Hydrocarbons ◽

Fluorescence Spectra ◽

Polycyclic Aromatic

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