A software framework for probabilistic sensitivity analysis for computationally expensive models
Tài liệu tham khảo
Mara, 2012, Variance-based sensitivity indices for models with dependent inputs, Rel. Eng. Syst. Safety, 107, 115, 10.1016/j.ress.2011.08.008
Saltelli, 2010, Variance based sensitivity analysis of model output. design and estimator for the total sensitivity index, Comput. Phys. Commun., 181, 259, 10.1016/j.cpc.2009.09.018
Vu-Bac, 2015, Uncertainty quantification for multiscale modeling of polymer nanocomposites with correlated parameters, Comp. Part B: Eng., 68, 446, 10.1016/j.compositesb.2014.09.008
Xu, 2007, Extending a global sensitivity analysis technique to models with correlated parameters, Comput. Stat. Data Anal., 51, 5579, 10.1016/j.csda.2007.04.003
Xu, 2008, Uncertainty and sensitivity analysis for models with correlated inputs, Rel. Eng. Syst. Safety, 1563, 10.1016/j.ress.2007.06.003
Kucherenko, 2012, Estimation of global sensitivity indices for models with dependent variables, Comput. Phys. Commun., 183, 937, 10.1016/j.cpc.2011.12.020
Most, 2012, Variance-based sensitivity analysis in the presence of correlated input variables
Sobol’, 1993, Sensitivity analysis for non-linear mathematical models, Math. Model. Comput. Exp., 1, 407
Schumann E.. http://comisef.wikidot.com/tutorial:correlateduniformvariates.
Vu-Bac, 2015, A unified framework for stochastic predictions of mechanical properties of polymeric nanocomposites, Comput. Mat. Sci., 96, 520, 10.1016/j.commatsci.2014.04.066
Ruppert, 2003
Ruppert D.. http://people.orie.cornell.edu/davidr/matlab/.
Lophaven, 2002, DACE A MATLAB Kriging toolbox
McKay, 1979, A comparison of three methods for selecting values of input variables in the analysis of output from a computer code, Technometrics, 21, 239
Iman, 1980, Small sample sensitivity analysis techniques for computer models with an application to risk assessment, Commun. Stat., A9, 1749, 10.1080/03610928008827996
Wyss, 1998, A user’s guide to LHS: Sandia’s latin hypercube sampling software.
Helton, 2003, Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems, Rel. Eng. Syst. Safety, 81, 23, 10.1016/S0951-8320(03)00058-9
Iman, 1982, A distribution-free approach to inducing rank correlation among input variables, Commun. Stat. - Simul. Comput., 11, 311, 10.1080/03610918208812265
Stein, 1987, Large sample properties of simulations using latin hypercube sampling, Technometrics, 29, 143, 10.1080/00401706.1987.10488205
Forrester, 2008
Vu-Bac, 2014, Stochastic predictions of bulk properties of amorphous polyethylene based on molecular dynamics simulations, Mech. Mat., 68, 70, 10.1016/j.mechmat.2013.07.021
Vu-Bac, 2014, Stochastic predictions of interfacial characteristic of polymeric nanocomposites (PNCs), Compos. Part B: Eng., 59, 80, 10.1016/j.compositesb.2013.11.014
Hutchinson, 1985, Smoothing noisy data with spline functions, Numer. Math., 47, 99, 10.1007/BF01389878
Carroll, 2000, Spatially-adaptive penalties for spline fitting, Aust. N. Z. J. Stat., 42, 205, 10.1111/1467-842X.00119
Dixon, 1978, The global optimization problem: an introduction, Towards Global Optim., 2, 1
Surjanovic S., Bingham D.. Virtual library of simulation experiments: test functions and datasets. Retrieved September 7, 2014, from http://www.sfu.ca/~ssurjano.
Bucher, 2009, Computational analysis of randomness in structural mechanics, 3
Ishigami, 1990, An importance quantification technique in uncertainty analysis for computer models, 398
Tüfekci, 2014, Prediction of full load electrical power output of a base load operated combined cycle power plant using machine learning methods, Int. J. Electr. Power Energ. Syst., 60, 126, 10.1016/j.ijepes.2014.02.027
Ghasemi, 2015, Optimum fiber content and distribution in fiber-reinforced solids using a reliability and NURBS based sequential optimization approach, Struct. Multidiscip. O., 51, 99, 10.1007/s00158-014-1114-y
Ghasemi, 2014, Uncertainties propagation in metamodel-based probabilistic optimization of CNT/polymer composite structure using stochastic multi-scale modeling, Comp. Mater. Sci., 85, 295, 10.1016/j.commatsci.2014.01.020
Wu, 2015, Torsional vibrations of a cylindrical foundation embedded in a saturated poroelastic half-space, Front. Struct. Civ. Eng., 9, 194, 10.1007/s11709-015-0292-z
Quayum, 2015, Computational model generation and RVE design of self-healing concrete, Front. Struct. Civ. Eng., 9, 383, 10.1007/s11709-015-0320-z
