Machine learning models for predicting PAHs bioavailability in compost amended soils
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Shaomin Wu | Guozhong Wu | Frederic Coulon | Simon J. T. Pollard | Cedric Kechavarzi | Hong Sui | Xingang Li | Shaomin Wu | S. Pollard | F. Coulon | Xingang Li | H. Sui | Guozhong Wu | C. Kechavarzi
[1] S. Pollard,et al. Influence of mature compost amendment on total and bioavailable polycyclic aromatic hydrocarbons in contaminated soils. , 2013, Chemosphere.
[2] Jie Shen,et al. In Silico Assessment of Chemical Biodegradability , 2012, J. Chem. Inf. Model..
[3] S. S. Mahapatra,et al. Artificial neural network (ANN) approach for modelling of arsenic (III) biosorption from aqueous solution by living cells of Bacillus cereus biomass , 2011 .
[4] L. Buydens,et al. Opening the kernel of kernel partial least squares and support vector machines. , 2011, Analytica chimica acta.
[5] H. Harms,et al. Dissolved organic carbon enhances the mass transfer of hydrophobic organic compounds from nonaqueous phase liquids (NAPLs) into the aqueous phase. , 2011, Environmental science & technology.
[6] Okan Ozgonenel,et al. Artificial neural network (ANN) approach for modeling Zn(II) adsorption from leachate using a new biosorbent , 2011 .
[7] J. Ivakpour,et al. Separation of toluene/n-heptane mixtures experimental, modeling and optimization , 2011 .
[8] Shaomin Wu,et al. Support vector regression for warranty claim forecasting , 2011, Eur. J. Oper. Res..
[9] Okan Ozgonenel,et al. The use of artificial neural networks (ANN) for modeling of adsorption of Cu(II) from industrial leachate by pumice , 2011 .
[10] André Carlos Ponce de Leon Ferreira de Carvalho,et al. Comparing machine learning classifiers in potential distribution modelling , 2011, Expert Syst. Appl..
[11] A. L. Swindell,et al. Bringing Bioavailability into Contaminated Land Decision Making: The Way Forward? , 2010 .
[12] K. Semple,et al. Biodegradation of PAHs in soil: Influence of chemical structure, concentration and multiple amendment. , 2010, Environmental pollution.
[13] S. Pollard,et al. When is a soil remediated? Comparison of biopiled and windrowed soils contaminated with bunker-fuel in a full-scale trial. , 2010, Environmental pollution.
[14] A. Etemad-Shahidi,et al. COMPARISON BETWEEN M5 MODEL TREE AND NEURAL NETWORKS FOR PREDICTION OF SIGNIFICANT WAVE HEIGHT IN LAKE SUPERIOR , 2009 .
[15] H. Harms,et al. Sorption to humic acids enhances polycyclic aromatic hydrocarbon biodegradation. , 2009, Environmental science & technology.
[16] P. Oleszczuk. Sorption of phenanthrene by sewage sludge during composting in relation to potentially bioavailable contaminant content. , 2009, Journal of hazardous materials.
[17] S. Pollard,et al. Development of an analytical procedure for weathered hydrocarbon contaminated soils within a UK risk-based framework. , 2008, Analytical chemistry.
[18] Christos S. Akratos,et al. An artificial neural network model and design equations for BOD and COD removal prediction in horizontal subsurface flow constructed wetlands , 2008 .
[19] P. Oleszczuk. Application of hydroxypropyl[β]cyclodextrin to evaluation of polycyclic aromatic hydrocarbon losses during sewage sludges composting , 2007, Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering.
[20] P. Oleszczuk. Investigation of potentially bioavailable and sequestrated forms of polycyclic aromatic hydrocarbons during sewage sludge composting. , 2007, Chemosphere.
[21] L. Buydens,et al. Visualisation and interpretation of Support Vector Regression models. , 2007, Analytica chimica acta.
[22] Farouq S Mjalli,et al. Use of artificial neural network black-box modeling for the prediction of wastewater treatment plants performance. , 2007, Journal of environmental management.
[23] E. Puglisi,et al. Bioavailability and degradation of phenanthrene in compost amended soils. , 2007, Chemosphere.
[24] I. Allan,et al. Prediction of mono- and polycyclic aromatic hydrocarbon degradation in spiked soils using cyclodextrin extraction. , 2006, Environmental pollution.
[25] F. Inal,et al. Artificial neural network predictions of polycyclic aromatic hydrocarbon formation in premixed n-heptane flames , 2006 .
[26] P. Putwain,et al. Woody biomass phytoremediation of contaminated brownfield land. , 2006, Environmental pollution.
[27] Zachary A. Hickman,et al. Towards a more appropriate water based extraction for the assessment of organic contaminant availability. , 2005, Environmental pollution.
[28] A. Wilkinson,et al. Prediction of polycyclic aromatic hydrocarbon biodegradation in contaminated soils using an aqueous hydroxypropyl‐β‐cyclodextrin extraction technique , 2005, Environmental toxicology and chemistry.
[29] R. Setiono,et al. Knowledge acquisition and revision via neural networks , 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).
[30] Kirk T. Semple,et al. Bioavailability of hydrophobic organic contaminants in soils: fundamental concepts and techniques for analysis , 2003 .
[31] Haralambos Sarimveis,et al. A neural network approach for the correlation of exhaust emissions from a diesel engine with diesel fuel properties , 2003 .
[32] Julian D. Olden,et al. Illuminating the “black box”: a randomization approach for understanding variable contributions in artificial neural networks , 2002 .
[33] Gary William Flake,et al. Efficient SVM Regression Training with SMO , 2002, Machine Learning.
[34] W. Rulkens,et al. The estimation of PAH bioavailability in contaminated sediments using hydroxypropyl-beta-cyclodextrin and Triton X-100 extraction techniques. , 2002, Chemosphere.
[35] J. Portal,et al. Effect of soil structure on the bioavailability of polycyclic aromatic hydrocarbons within aggregates of a contaminated soil , 2001 .
[36] A Durán,et al. Simulation of atmospheric PAH emissions from diesel engines. , 2001, Chemosphere.
[37] F. Kopinke,et al. Sorption of pyrene to dissolved humic substances and related model polymers. 1. Structure--property correlation. , 2001, Environmental science & technology.
[38] K. Jones,et al. Nonexhaustive Cyclodextrin-Based Extraction Technique for the Evaluation of PAH Bioavailability , 2000 .
[39] JOHANNES FÜRNKRANZ,et al. Separate-and-Conquer Rule Learning , 1999, Artificial Intelligence Review.
[40] Desmond Fletcher,et al. Forecasting with neural networks: An application using bankruptcy data , 1993, Inf. Manag..
[41] Fulvia Tambone,et al. Use of biosurfactants from urban wastes compost in textile dyeing and soil remediation. , 2009, Waste management.
[42] B. Antízar-Ladislao,et al. Laboratory studies of the remediation of polycyclic aromatic hydrocarbon contaminated soil by in-vessel composting. , 2005, Waste management.
[43] Dimitri P. Solomatine,et al. Neural networks and M5 model trees in modelling water level-discharge relationship , 2005, Neurocomputing.
[44] B. Maliszewska-Kordybach,et al. Soil Quality, Sustainable Agriculture and Environmental Security in Central and Eastern Europe , 2000 .
[45] K. Jones,et al. Organic chemicals in contaminated land : analysis, significance and research priorities. , 1996 .
[46] Christopher M. Bishop,et al. Neural networks for pattern recognition , 1995 .