Topographic uncertainty quantification for flow-like landslide models via stochastic simulations

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Bibliographic citation: In: 10.5194/nhess-20-1441-2020

Event: Veröffentlichung

(where): Aachen

(who): Universitätsbibliothek der RWTH Aachen

(when): 2020

Creator: Zhao, Hu
Kowalski, Julia

DOI: 10.18154/RWTH-2020-07483

URN: urn:nbn:de:101:1-2020080423323796374162

Rights: Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 25.03.2025, 1:46 PM CET

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Zhao, Hu
Kowalski, Julia
Universitätsbibliothek der RWTH Aachen

Time of origin

2020

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Topographic uncertainty quantification for flow-like landslide models via stochastic simulations

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Other Objects (12)

Topographic uncertainty in mass flow simulations - preliminary results

Adaptive approximations for high-dimensional uncertainty quantification in stochastic parametric electromagnetic field simulations

Gaussian processes for sensitivity analysis, Bayesian inference, and uncertainty quantification in landslide research

Coupling between stochastic particle transport models and topographic thin film growth

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Derek Hardie: Landslide

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Topographic uncertainty in mass flow simulations - preliminary results

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Gaussian processes for sensitivity analysis, Bayesian inference, and uncertainty quantification in landslide research

Coupling between stochastic particle transport models and topographic thin film growth

Quantification of ground motions by broadband simulations

Derek Hardie: Landslide

Spatial analysis, quantification and evaluation of developments in settlement structure based on topographic geodata

Stochastic adaptive control : results and simulations

Numerical simulations and uncertainty quantification for cloud simulation

TWRM-TOPOGRAPHIC : Abschlußbericht

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Adaptive approximations for high-dimensional uncertainty quantification in stochastic parametric electromagnetic field simulations

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Derek Hardie: Landslide

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