A review of techniques for parameter sensitivity analysis of environmental models

By D. Hamby. 1994

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Citations in the corpus

Hyper-Parameter Optimization: A Review of Algorithms and Applications (2020, background): “A sensitivity test is suggested (Hamby, 1994; Breierova and Choudhari, 1996) to ensure the influence of a certain hyper-parameter.”
Is my model good enough? Best practices for verification and validation of musculoskeletal models and simulations of movement. (2015, background): “The direct approach is a differential analysis, which determines the analytic relationship between inputs and outputs [20].”
The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020, unknown): “Another example is the commonly called ‘Regional Sensitivity Analysis ’ (RSA) which, rather than fixing inputs, defines conditional distributions based on thresholds for the model response (Spear et al., 1994; Hamby, 1994).”
Sensitivity in risk analyses with uncertain numbers. (2006, methodology): “For example, the sampling-based methods of sensitivity analysis described by Helton et al. (2006b) are especially useful for tracking analyses that match which particular inputs correspond to outcomes of special interest.”
Comparison of two different approaches of sensitivity analysis (2002, methodology): “Therefore sensitivity analysis as an instrument for the assessment of the input parameters with respect to their impact on model output is useful not only for model development, but also for model validation and reduction of uncertainty (Hamby, 1994).”
Predicting crop yields and soil‐plant nitrogen dynamics in the US Corn Belt (2020, methodology): “Sensitivity of grain yield, soil nitrate and other variables were assessed using a relative sensitivity index (Hamby, 1994).”
Visualization and Visual Analysis of Multifaceted Scientific Data: A Survey (2013, unknown): “The goals of such a sensitivity analysis include [34]: the identification of model parameters that require additional research, which also reduces the output uncertainty; identifying control parameters that are strongly correlated with the simulation output; or finding insignificant parameters that…”
Biodiesel synthesis from Ceiba pentandra oil by microwave irradiation-assisted transesterification: ELM modeling and optimization (2020, background): “Sensitivity analysis is carried out to determine (1) which parameters require additional research to strengthen the knowledge base, which will reduce output uncertainty, (2) which parameters are insignificant and can be eliminated from the final model, (3) which inputs or parameters have a significa”
The emergence of new technology-based industries: the case of fuel cells and its technological relatedness to regional knowledge bases (2016, methodology): “For 13 It was not possible to perform more complex sensitivity analysis (as e.g. reviewed by Hamby (1994)) because these are not available for the negative binomial regression for panel data command (xtnbreg) in Stata. at D T U L ibrary on June 10, 2016 http://joeg.oxfordjournals.org/ D ow nloaded…”
Latin Hypercube Sampling and Partial Rank Correlation Coefficient Analysis Applied to an Optimal Control Problem (2012, methodology): “Compared to ordinary Partial Correlation Coefficient procedure, PRCC is considered to be more powerful at determining the sensitivity of a parameter that is strongly monotonic yet highly nonlinear [4].”
Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications (2015, unknown): “In general, when referring to the extent that a parameter affects the model output, we can use the terms ‘‘sensitive’’, ‘‘important’’, ‘‘most influential’’, ‘‘major contributor’’, ‘‘effective’’, or ‘‘correlated’’ interchangeably (Hamby, 1994).”
Survey of modeling and optimization strategies to solve high-dimensional design problems with computationally-expensive black-box functions (2010, methodology): “Hamby (1994) reviewed the techniques for sensitivity analysis of environmental models .”
A performance comparison of sensitivity analysis methods for building energy models (2015, methodology): “Table 1: SA methods investigated in this study and their basic features (adapted from (Morris 1991; Sobol 1993; Hamby 1994; Frey et al. 2003; Giglioli and Saltelli 2008; Tian 2013; Saltelli et al. 2004; Nossent el al. 2011))”