Publications
Chosen filters:
Chosen filters:
Machine-learning-based hybrid random-fuzzy uncertainty quantification for EMC and SI assessment Ghent University
Uncertainty in training image-based inversion of hydraulic head data constrained to ERT data : workflow and case study Ghent University
Impact of GCM structure uncertainty on hydrological processes in an arid area of China Ghent University
Experimental uncertainty analysis of monopile scour protection stability tests Ghent University
Hydraulic experiments using physical scale models of monopile scour protections typically have high ex-perimental uncertainties and data scattering. These uncertainties may severely affect the accuracy of the experimental results and need to be analysed quantitatively. This paper presents a study on the quantification of experimental uncertainties in monopile scour protection damage tests following the Guide to the expression of Uncertainty in ...
Uncertainty quantification for the aeroacoustics of rotating blades in the time domain Vrije Universiteit Brussel
Aeroacoustics has received great attention in the past decade, owing to the ever stricter noise regulations. Despite the stochastic nature of most aeroacoustic systems, non-deterministic investigations in regards to computational aeroacoustics (CAA) are limited. In this paper, uncertainty quantification has been achieved for the noise propagation stage of hybrid CAA, and also on the noise prediction of a non-lifting helicopter rotor in hover. ...
Incorporating land-use mapping uncertainty in remote sensing based calibration of land-use change models Vrije Universiteit Brussel KU Leuven
Building urban growth models typically involves a process of historic calibration based on historic time series of land-use maps, usually obtained from satellite imagery. Both the remote sensing data analysis to infer land use and the subsequent modelling of land-use change are subject to uncertainties, which may have an impact on the accuracy of future land-use predictions. Our research aims to quantify and reduce these uncertainties by means ...
Quantifying and reducing epistemic uncertainty of passive acoustic telemetry data from longitudinal aquatic systems Flanders Marine Institute Ghent University
Passive acoustic telemetry data are used to study animal movement in aquatic environments, but tools to process the data are limited. In areas that are too large to be fully covered by the limited detection ranges of receivers or acoustic listening stations, researchers generally assume that animals are residing in an area when they are detected frequently at specific receivers. There is, however, no consensus on how this area and frequency ...
Transmission of uncertainty shocks: Learning from heterogeneous responses on a panel of EU countries Vrije Universiteit Brussel
Numerous recent studies, starting with Bloom (2009), highlight the impact of uncertainty on economic activity. These studies mostly focus on individual countries, while cross-country evidence is scarce. In this paper, we use a set of (panel) BVAR models to study the effect of uncertainty shocks on economic developments in EU Member States. We derive new proxies of domestic uncertainty for individual Member States using dispersion of answers ...
Uncertainty propagation in vegetation distribution models based on ensemble classifiers Ghent University University of Antwerp
Ensemble learning techniques are increasingly applied for species and vegetation distribution modelling, often resulting in more accurate predictions. At the same time, uncertainty assessment of distribution models is gaining attention. In this study, Random Forests, an ensemble learning technique, is selected for vegetation distribution modelling based on environmental variables. The impact of two important sources of uncertainty, that is the ...