Emulation techniques for the reduction and sensitivity analysis of complex environmental models

By Marco Ratto, A. Castelletti, Andrea Pagano. 2012

118 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Management Science and Operations Research, Statistics and Probability

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Citations in the corpus

An evaluation of adaptive surrogate modeling based optimization with two benchmark problems (2014, background): “Also, some other papers generalized the framework of surrogate modeling and using this for sensitivity analysis and optimization of complex environmental models (Castelletti et al., 2012; Ratto et al., 2012; Carnevale et al., 2012).”
Review of surrogate modeling in water resources (2012, methodology): “More recent literature uses DACE to refer to the suite of all metamodel/ emulation techniques [e.g., Ratto et al., 2012; Simpson et al., 2008].”
Selecting among five common modelling approaches for integrated environmental assessment and management (2013, methodology): “A possible solution is to simplify the model by use of a metamodel (PiñerosGarcet et al., 2006; Ratto et al., 2012), but even if this is possible, another requirement is to be able to formally define an objective function to be optimised.”
Sensitivity analysis of environmental models: A systematic review with practical workflow (2014, background): “The interested reader is referred to Forrester et al. (2008) for a general introduction to emulation modelling, and Ratto et al. (2012) for a review of its application in SA.”
Managing computational complexity using surrogate models: a critical review (2020, background): “Another special issue publication regarding surrogate modeling is a thematic journal issue focusing on surrogate modeling for sensitivity analyses and the reduction of complex environmental models (Ratto et al. 2012).”
Characterising performance of environmental models (2013, methodology): “For more information on sensitivity analysis, see Saltelli et al. (2000), Norton (2008), Frey and Patil (2002), Saltelli and Annoni (2010), Shahsavani and Grimvall (2011), Makler-Pick et al. (2011), Yang (2011), Nossent et al. (2011), Ratto et al. (2012) and Ravalico et al. (2010).”
Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions (2014, background): “…an extensive review of surrogate modelling in water resources and recent developments and applications to environmental systems are also presented in a special issue on “Emulation techniques for the reduction and sensitivity analysis of complex environmental models” (see Ratto et al., 2012).”