The construction and implementation of metamodels

By Robert W. Blanning. 1975

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Citations in the corpus

An evaluation of adaptive surrogate modeling based optimization with two benchmark problems (2014, methodology): “Some fields also refer to the surrogate modeling as function approximation, meta-modeling, response surface method, or model emulation (Blanning, 1975; O'Hagan, 2006).”
A machine learning framework to forecast wave conditions (2017, unknown): “These have alternately been called “metamodels” (Blanning, 1975; Kleijnen, 2009), “model emulators” (O'Hagan, 2006), and “proxy models” (Bieker et al.”
Stochastic sampling design using a multi-objective genetic algorithm and adaptive neural networks (2009, methodology): “The use of metamodels to reduce the computational times in optimization processes was proposed by Blanning (1975).”
Review of surrogate modeling in water resources (2012, background): “Response surface surrogates may also be referred to as ‘‘metamodels’’ [Blanning, 1975; Kleijnen, 2009] as a response surface surrogate is a ‘‘model of a model.’’”
Future research challenges for incorporation of uncertainty in environmental and ecological decision-making (2008, background): “Metamodels, first proposed by Blanning (1975), are models of simulation models.”
Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions (2014, background): “…a nondynamic mapping (regression) of the complex model inputs into the outputs, namely objective functions and/or constraints (Bieker et al., 2007; Blanning, 1975; Broad et al., 2005, 2010; Gorissen et al., 2010; Keating et al., 2010; Kleijnen, 2009; Laloy et al., 2013; Queipo et al., 2005; Yan…”