An Example of Augmenting Regional Sensitivity Analysis Using Machine Learning Software

[1]  Robert B. Gramacy,et al.  Ja n 20 08 Bayesian Treed Gaussian Process Models with an Application to Computer Modeling , 2009 .

[2]  Keith Beven,et al.  Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology , 2001 .

[3]  G. Hornberger Eutrophication in peel inlet—I. The problem-defining behavior and a mathematical model for the phosphorus scenario , 1980 .

[4]  Andy Liaw,et al.  Classification and Regression by randomForest , 2007 .

[5]  Xi Chen,et al.  Uncertainty analysis of a semi-distributed hydrologic model based on a Gaussian Process emulator , 2018, Environ. Model. Softw..

[6]  D. Hamby A review of techniques for parameter sensitivity analysis of environmental models , 1994, Environmental monitoring and assessment.

[7]  Eric R. Ziegel,et al.  The Elements of Statistical Learning , 2003, Technometrics.

[8]  M. B. Beck,et al.  Water quality modeling: A review of the analysis of uncertainty , 1987 .

[9]  Nong Shang,et al.  Parameter uncertainty and interaction in complex environmental models , 1994 .

[10]  Aynom T. Teweldebrhan,et al.  Coupled machine learning and the limits of acceptability approach applied in parameter identification for a distributed hydrological model , 2019, Hydrology and Earth System Sciences.

[11]  R C Spear,et al.  Modeling benzene pharmacokinetics across three sets of animal data: parametric sensitivity and risk implications. , 1991, Risk analysis : an official publication of the Society for Risk Analysis.

[12]  Trevor Hastie,et al.  An Introduction to Statistical Learning , 2013, Springer Texts in Statistics.

[13]  Saman Razavi,et al.  Insights into sensitivity analysis of Earth and environmental systems models: On the impact of parameter perturbation scale , 2017, Environ. Model. Softw..

[14]  R. C. Spear,et al.  Monte Carlo method for component sizing , 1970 .

[15]  Lori White,et al.  A Systematic Approach for Variable Selection With Random Forests: Achieving Stable Variable Importance Values , 2017, IEEE Geoscience and Remote Sensing Letters.

[16]  Guang Yang,et al.  DGSA: A Matlab toolbox for distance-based generalized sensitivity analysis of geoscientific computer experiments , 2016, Comput. Geosci..

[17]  H. Gupta,et al.  A new framework for comprehensive, robust, and efficient global sensitivity analysis: 1. Theory , 2016 .

[18]  John P. Norton Algebraic sensitivity analysis of environmental models , 2008, Environ. Model. Softw..

[19]  Peng Gong,et al.  The interplay of climate, intervention and imported cases as determinants of the 2014 dengue outbreak in Guangzhou , 2017, PLoS neglected tropical diseases.

[20]  Line H. Clemmensen,et al.  Forest Floor Visualizations of Random Forests , 2016, ArXiv.

[21]  A. Aulia,et al.  A Random Forests-based sensitivity analysis framework for assisted history matching , 2019, Journal of Petroleum Science and Engineering.

[22]  Brandon M. Greenwell pdp: An R Package for Constructing Partial Dependence Plots , 2017, R J..

[23]  Keith Beven,et al.  The future of distributed models: model calibration and uncertainty prediction. , 1992 .

[24]  Saman Razavi,et al.  Revisiting the Basis of Sensitivity Analysis for Dynamical Earth System Models , 2018, Water Resources Research.

[25]  Daniel W. Meyer,et al.  Density estimation with distribution element trees , 2016, Statistics and Computing.

[26]  Tarn Duong,et al.  ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R , 2007 .

[27]  A. Raftery,et al.  Inference for Deterministic Simulation Models: The Bayesian Melding Approach , 2000 .

[28]  Paul G. Constantine,et al.  Reprint of: Active subspaces for sensitivity analysis and dimension reduction of an integrated hydrologic model , 2016, Comput. Geosci..

[29]  Jef Caers,et al.  Quantifying Asymmetric Parameter Interactions in Sensitivity Analysis: Application to Reservoir Modeling , 2014, Mathematical Geosciences.

[30]  Mark Sharefkin,et al.  Uncertainty and Forecasting of Water Quality: Reflections of an Ignorant Bayesian , 1983 .

[31]  J. Friedman Greedy function approximation: A gradient boosting machine. , 2001 .

[32]  R. Spear Eutrophication in peel inlet—II. Identification of critical uncertainties via generalized sensitivity analysis , 1980 .

[33]  William B. March,et al.  MLPACK: a scalable C++ machine learning library , 2012, J. Mach. Learn. Res..

[34]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[35]  Jim W. Hall,et al.  Sensitivity analysis of environmental models: A systematic review with practical workflow , 2014, Environ. Model. Softw..