Machine learning models for predicting PAHs bioavailability in compost amended soils

[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 .