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[PDF] Top 20 Sensitivity analysis of spatial models using geostatistical simulation

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Sensitivity analysis of spatial models using geostatistical simulation

Sensitivity analysis of spatial models using geostatistical simulation

... part of total variability of model output? To answer these questions, this article aims at determining, in the context of spatial GSA, how sensitivity indices depend on the covariance ... Voir le document complet

13

Latin Hypercube Sampling of Gaussian random field for Sobol' global sensitivity analysis of models with spatial inputs and scalar output

Latin Hypercube Sampling of Gaussian random field for Sobol' global sensitivity analysis of models with spatial inputs and scalar output

... one of the few global sensitivity analysis methods that is suitable for complex models with spatially distributed ...number of model runs to compute sensitivity indices: in the ... Voir le document complet

5

Change of support effects in spatial variance-based sensitivity analysis

Change of support effects in spatial variance-based sensitivity analysis

... for models where both inputs and out- put can be described as real valued random variables, some recent work has extended GSA to environmental models for which both the inputs and output are spatially ... Voir le document complet

46

Sensitivity analysis of spatial models: application to cost-benefit analysis of flood risk management plans

Sensitivity analysis of spatial models: application to cost-benefit analysis of flood risk management plans

... Introduction Sensitivity analysis (SA) techniques are increasingly recognized as useful tools for the modeller: they allow robustness of model predictions to be checked and help identifying the input ... Voir le document complet

296

Initial spatial conditions in simulation models: the missing leg of sensitivity analyses?

Initial spatial conditions in simulation models: the missing leg of sensitivity analyses?

... Although simulation models of geographical systems in general and agent-based models in par- ticular represent a fantastic opportunity to explore socio-spatial behaviours and to test a ... Voir le document complet

6

Using Probabilistic Relational Models to Generate Synthetic Spatial or Non-spatial Databases

Using Probabilistic Relational Models to Generate Synthetic Spatial or Non-spatial Databases

... generation of such artificial data since a long time. A number of research works deal with artificial data generation for specific domains such as credit scoring [5], genetic study [6], intrusion detection ... Voir le document complet

13

Global sensitivity analysis for models with spatially dependent outputs

Global sensitivity analysis for models with spatially dependent outputs

... model of 90 Sr transport in groundwater was developed for the RRC Kur- chatov Institute (KI) radwaste disposal site (Volkova et ...prediction of further contamination plume spreading since 2002 ... Voir le document complet

39

A performance comparison of sensitivity analysis methods for building energy models

A performance comparison of sensitivity analysis methods for building energy models

... 26 sensitivity indices encountered difficulty with non-monotonic problems while non- monotonicity may present in a building energy ...SA of building energy models, expensive computational cost may be ... Voir le document complet

30

Causality and sensitivity analysis in distributed design simulation

Causality and sensitivity analysis in distributed design simulation

... Sensitivity is estimated by linear regression analysis and a perturbation method, which transfers the problem into a frequency domain by generating periodic perturbations.. Varying[r] ... Voir le document complet

111

Sensitivity analysis and uncertainty quantification for environmental models

Sensitivity analysis and uncertainty quantification for environmental models

... Résumé. Les modèles environnementaux contiennent souvent des entrées-sorties complexes de par leur nature dynamique et spatiale, ce qui soulève des problèmes spécifiques pour leurs analyses d’in- certitude et de ... Voir le document complet

23

Sensitivity analysis and uncertainty quantification for environmental models

Sensitivity analysis and uncertainty quantification for environmental models

... impact of flood risk ...range of flood scenarios of various magnitudes ...intervals of these scenarios are computed from a series of annual maximum flows at a gauging ...Estimation ... Voir le document complet

23

Numerical simulation and sensitivity analysis of thermally induced flow instabilities

Numerical simulation and sensitivity analysis of thermally induced flow instabilities

... NRC Publications Archive Archives des publications du CNRC This publication could be one of several versions: author’s original, accepted manuscript or the publisher’s version. / La version de cette publication ... Voir le document complet

4

Global Sensitivity Analysis of Stochastic Computer Models with joint metamodels

Global Sensitivity Analysis of Stochastic Computer Models with joint metamodels

... computer models often take as inputs a high number of numerical variables and physical variables, and give several outputs (scalars or ...opment of such computer models, its analysis, ... Voir le document complet

17

Sensitivity Analysis of Parallel Manipulators Using an Interval Linearization Method

Sensitivity Analysis of Parallel Manipulators Using an Interval Linearization Method

... sources of errors have been identified and integrated in dedicated computational ...sources of errors we find manufacturing errors, joint clearances, and backlashes in the ...The sensitivity ... Voir le document complet

40

Spatial analysis of groundwater quality using self-organizing maps

Spatial analysis of groundwater quality using self-organizing maps

... visualization of SOM-analysis and hydrochemical characteristics, groundwater samples were clustered into three clusters, which revealed three basic representative water types: freshwater (cluster 1), ... Voir le document complet

1

Using Markov Models to Mine Temporal and Spatial Data

Using Markov Models to Mine Temporal and Spatial Data

... variations of the a posteriori probability as a function of the index in the nucleotide sequence are ...total of 146 atypical regions were ...total of 362 genes of 1915 (the whole gene ... Voir le document complet

26

Design and simulation of divided wall column: Experimental validation and sensitivity analysis

Design and simulation of divided wall column: Experimental validation and sensitivity analysis

... design of divided wall columns or fully thermally coupled distillations is more complex than traditional distillation because it has more degrees of ...number of papers have been published on the ... Voir le document complet

20

Simplified converters models for the analysis and simulation of large transmission systems using 100% power electronics

Simplified converters models for the analysis and simulation of large transmission systems using 100% power electronics

... Conclusion In this paper, a MOR reduction that preserves the physical structure of the system is proposed and applied to a PE converter. The obtained reduced model is then validated on a two-converter system to ... Voir le document complet

11

OPTIMAL CONTROL AND SENSITIVITY ANALYSIS OF A BUILDING USING ADJOINT METHODS

OPTIMAL CONTROL AND SENSITIVITY ANALYSIS OF A BUILDING USING ADJOINT METHODS

... use of an adjoint ...to sensitivity studies of the optimal control ...theory of optimal control of sys- tems governed by partial differential equations (Lions, ... Voir le document complet

9

Sensitivity Analysis Using a Fixed Point Interval Iteration

Sensitivity Analysis Using a Fixed Point Interval Iteration

... Parametrization of the Hansen-Sengupta Existence Test Functions with parameters are considered in this ...function of n variables and p ...usage of the Kaucher arithmetic) was proposed and used in ... Voir le document complet

6

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