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math.OC2024★ 1 cited
Adaptive discretization algorithms for locally optimal experimental design
Jochen Schmid, Philipp Seufert, Michael Bortz
We develop adaptive discretization algorithms for locally optimal experimental design of nonlinear prediction models. With these algorithms, we refine and improve a pertinent state…
math.OC2024
Sequential optimal experimental design for vapor-liquid equilibrium modeling
Martin Bubel, Jochen Schmid, Volodymyr Kozachynskyi +2
We propose a general methodology of sequential locally optimal design of experiments for explicit or implicit nonlinear models, as they abound in chemical engineering and, in parti…