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المصدر: Journal of the Serbian Chemical Society, Vol 86, Iss 7-8, Pp 673-684 (2021)
مصطلحات موضوعية: Quantitative structure–activity relationship, Artificial neural network, General Chemistry, Pesticide, 010402 general chemistry, 01 natural sciences, Pearson product-moment correlation coefficient, 0104 chemical sciences, descriptors, Support vector machine, Chemistry, symbols.namesake, Aqueous solubility, genetic algorithm, statistical methods, symbols, Biological system, QD1-999, agrochemicals, Mathematics
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b8841bbdf4040929988690fbff3fc8b1
https://doi.org/10.2298/jsc200618066b -
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المصدر: International Journal of Safety and Security Engineering. 10:389-396
مصطلحات موضوعية: Quantitative Structure Property Relationship, Series (mathematics), Applied mathematics, Pesticide, Safety, Risk, Reliability and Quality, Constant (mathematics), General Environmental Science, Mathematics
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::2f6fd23f3812284c3efdbb9099ffef6e
https://doi.org/10.18280/ijsse.100311 -
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المؤلفون: Amel Bouakkadia, Djelloul Messadi, Rana Amiri
المصدر: Journal of the Serbian Chemical Society, Vol 85, Iss 4, Pp 467-480 (2020)
مصطلحات موضوعية: octanol/water partition coefficient, Octanol, Quantitative structure–activity relationship, Statistical parameter, General Chemistry, 010402 general chemistry, 01 natural sciences, 0104 chemical sciences, lcsh:Chemistry, molecular descriptors, chemistry.chemical_compound, qspr methods, lcsh:QD1-999, chemistry, Test set, Molecular descriptor, SDEP, Linear regression, Partition (number theory), Biological system, Mathematics
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::86eaeeca93610a919d5d62b9089018a8
https://doi.org/10.2298/jsc190610090a -
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المؤلفون: Djelloul Messadi, Nabil Bouarra, Soumaya Kherouf, Amel Bouakkadia
المصدر: Journal of the Serbian Chemical Society, Vol 84, Iss 6, Pp 575-590 (2019)
مصطلحات موضوعية: multiple linear regression, Quantitative structure–activity relationship, phenols, General Chemistry, 010402 general chemistry, 01 natural sciences, 0104 chemical sciences, lcsh:Chemistry, Nonlinear system, chemistry.chemical_compound, lcsh:QD1-999, chemistry, Multicollinearity, QSPR, aqueous solubility, Molecular descriptor, Linear regression, Aqueous solubility, Cutoff, Phenol, Biological system, artificial neural network, Mathematics
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::17d0f597f54e611390fb61de18fdb78d
https://doi.org/10.2298/jsc180820016k -
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المصدر: Energy Procedia. 157:551-560
مصطلحات موضوعية: Octanol, Multilinear map, Quantitative structure–activity relationship, Molecular model, Artificial neural network, 020209 energy, 02 engineering and technology, Pesticide, Soil contamination, Partition coefficient, chemistry.chemical_compound, 020401 chemical engineering, chemistry, 0202 electrical engineering, electronic engineering, information engineering, 0204 chemical engineering, Biological system, Mathematics
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المصدر: Journal of the Serbian Chemical Society, Vol 84, Iss 12, Pp 1405-1414 (2019)
مصطلحات موضوعية: multiple linear regression, Quantitative structure–activity relationship, Vapor pressure, log pv, Regression analysis, General Chemistry, Plot (graphics), lcsh:Chemistry, molecular descriptors, lcsh:QD1-999, Molecular descriptor, Test set, Linear regression, vocs, Biological system, Mathematics, Applicability domain
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cd65b9b85827e99c64f9dc84a9d28ccb
http://www.doiserbia.nb.rs/img/doi/0352-5139/2019/0352-51391900059Z.pdf -
7Modeling and Prediction of Gas Chromatography Relative Retention Times of Volatile Organic Compounds
المؤلفون: Mounia Zine Mounia Zine, Amel Bouakkadia Amel Bouakkadia, Leila Lourici and Djelloul Messadi Leila Lourici and Djelloul Messadi
المصدر: Journal of the chemical society of pakistan. 42:447-447
مصطلحات موضوعية: General Chemistry
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::00cd90b8e6f238200bb2c1a9c89cb46f
https://doi.org/10.52568/000645/jcsp/42.03.2020 -
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المؤلفون: Djelloul Messadi, Leila Lourici, Amel Bouakkadia
المصدر: Management of Environmental Quality: An International Journal. 28:579-592
مصطلحات موضوعية: Quantitative structure–activity relationship, 010405 organic chemistry, Public Health, Environmental and Occupational Health, Linear model, 02 engineering and technology, Management, Monitoring, Policy and Law, 021001 nanoscience & nanotechnology, 01 natural sciences, 0104 chemical sciences, Toxicology, Data set, Support vector machine, Test set, Molecular descriptor, Linear regression, Outlier, 0210 nano-technology, Biological system, Mathematics
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المؤلفون: Amel Bouakkadia, Leila Lourici, Djelloul Messadi, Rana Amiri
المصدر: Egyptian Journal of Chemistry.
مصطلحات موضوعية: Octanol, Quantitative structure–activity relationship, 06 humanities and the arts, 010501 environmental sciences, 0603 philosophy, ethics and religion, 01 natural sciences, Support vector machine, Data set, Partition coefficient, chemistry.chemical_compound, chemistry, Molecular descriptor, Test set, 060302 philosophy, Linear regression, Biological system, 0105 earth and related environmental sciences, Mathematics
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::d746f5e15a82a39e517bec44a1764012
https://doi.org/10.21608/ejchem.2019.4976.1446 -
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المؤلفون: Hamza Haddag, Nabil Bouarra, Amel Bouakkadia, Djelloul Messadi
المصدر: Synthèse : Revue des Sciences et de la Technologie. :12-21
مصطلحات موضوعية: Quantitative structure–activity relationship, Correlation coefficient, Feature selection, 02 engineering and technology, 010402 general chemistry, 021001 nanoscience & nanotechnology, 01 natural sciences, 0104 chemical sciences, Set (abstract data type), Test set, Molecular descriptor, Ordinary least squares, Linear regression, Econometrics, 0210 nano-technology, Biological system, Mathematics
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::07dcb8341734f45a4bbc307a6bafa4f9
https://doi.org/10.12816/0027948