Sensitivity analysis for chemical models.

By Andrea Saltelli, Marco Ratto, Stefano Tarantola, Francesca Campolongo. Chemical Reviews, 2005

668 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/c3182746b919399ed250b980059e04498fb10785

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In Computational Theory and Mathematics

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Citations in the corpus

Sensitivity analysis of environmental models: A systematic review with practical workflow (2014, methodology): “…review in this regard are the introduction to sensitivity assessment of simulation models by Norton (2015), the literature reviews (with a focus on the chemical modelling literature) by Saltelli et al. (2005, 2012) and the review of recent methodological advances by Borgonovo and Plischke (2016).”
A methodology for performing global uncertainty and sensitivity analysis in systems biology. (2008, background): “See Iman and Helton, (1988) and Saltelli et al. (2000) for details on each of these approaches and Cacuci and Ionescu-Bujor (2004), Draper (1995), Helton (1993) and Saltelli et al. (2005) for more general reviews on US analysis.”
Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications (2015, neutral): “…of the analysis, (b) the number of uncertain input factors, (c) the degree of complexity of the model, (d) the computing time for a single model simulation, and (e) the analyst’s time available to perform a SA (Cacuci et al., 2013; Saltelli et al., 2005, 2012; Wallach et al., 2006; Zajac, 2010).”
Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2010, background): “The total sensitivity indices have been introduced by Homma and Saltelli [11], although the concept was proposed in [15] (see reviews [10,29,32] or Chapter eight in [27]).”
From screening to quantitative sensitivity analysis. A unified approach (2011, methodology): “A wide range of global SA methods is available (for reviews see [25,28,31,27,11,21]), ranging from qualitative screening methods [18,3,29,15] to quantitative techniques based on variance decomposition [34,12,24,19].”
A structure optimisation algorithm for feedforward neural network construction (2013, methodology): “The variance, Dyq, is computed from the Fourier translation [37]”
An overview of methods to evaluate uncertainty of deterministic models in decision support (2015, neutral): “This can be achieved by using various approaches ranging from simple one-factor-at-a-time methods to more comprehensive approaches, usually based on MC methods (e.g. Saltelli et al., 2005; Cariboni et al., 2007; Yang, 2011).”
Sensitivity analysis approaches applied to systems biology models. (2011, methodology): “Sensitivity analysis has a long history and it has been widely applied in different ﬁelds such as environmental modelling study [6], economic modelling for decisions making [7], chemical kinetics [8–10] and biological modelling analysis [11, 12].”
An effective screening design for sensitivity analysis of large models (2007, background): “Different approaches can be followed to test the sensitivity of a model (Saltelli et al., 2004, 2005; Cacuci and Ionesco-Bujor, 2004).”
A fully multiple-criteria implementation of the Sobol' method for parameter sensitivity analysis (2012, methodology): “With STi, we no longer have to limit the analysis to additive models [Saltelli et al., 2005].”