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Jiao, Long (2012) QSPR Study on the Soil-Water Partition Coefficient of Polychlorinated Biphenyls by Using Artificial Neural Network. Advanced Materials Research, 455. 930-934 doi:10.4028/www.scientific.net/amr.455-456.930

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Reference TypeJournal (article/letter/editorial)
TitleQSPR Study on the Soil-Water Partition Coefficient of Polychlorinated Biphenyls by Using Artificial Neural Network
JournalAdvanced Materials Research
AuthorsJiao, LongAuthor
Year2012 (January)Volume455
PublisherTrans Tech Publications, Ltd.
DOIdoi:10.4028/www.scientific.net/amr.455-456.930Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID11674018Long-form Identifiermindat:1:5:11674018:4
GUID0
Full ReferenceJiao, Long (2012) QSPR Study on the Soil-Water Partition Coefficient of Polychlorinated Biphenyls by Using Artificial Neural Network. Advanced Materials Research, 455. 930-934 doi:10.4028/www.scientific.net/amr.455-456.930
Plain TextJiao, Long (2012) QSPR Study on the Soil-Water Partition Coefficient of Polychlorinated Biphenyls by Using Artificial Neural Network. Advanced Materials Research, 455. 930-934 doi:10.4028/www.scientific.net/amr.455-456.930
In(n.d.) Advanced Materials Research Vol. 455. Trans Tech Publications, Ltd.

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Jiao, Long (2012) QSPR Study on the Soil-Water Partition Coefficient of Polychlorinated Biphenyls by Using Artificial Neural Network. Advanced Materials Research, 455. 930-934 doi:10.4028/scientific5/amr.455-456.930
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Jiao, Long (2012) QSPR Studies on n-Octanol/Water Partition Coefficient of Polychlorinated Biphenyls by Using Artificial Neural Network. Advanced Materials Research, 455. 925-929 doi:10.4028/scientific5/amr.455-456.925
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Ye, Yin, Yang, Zhen, Dang, Xiao Peng, Liu, Zi Huai (2012) The Progress of Research on Soil Heavy Metals. Advanced Materials Research, 455. 1285-1288 doi:10.4028/www.scientific.net/amr.455-456.1285
Qiao, Shu, Xie, Kun, Fu, Chuan, Pan, Jie (2011) QSPR Study on n-Octanol/Water Partition Coefficient of PCDD/Fs by Three-Dimensional Holographic Vector of Atomic Interaction Field. Advanced Materials Research, 356. 83-88 doi:10.4028/www.scientific.net/amr.356-360.83
 
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