Searched for: subject%3A%22probabilistic%255C+modelling%22
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Seis, W.A.A. (author), ten Veldhuis, Marie-claire (author), Rouault, Pascale (author), Steffelbauer, D.B. (author), Medema, G.J. (author)
Short-term fecal pollution events are a major challenge for managing microbial safety at recreational waters. Long turn-over times of current laboratory methods for analyzing fecal indicator bacteria (FIB) delay water quality assessments. Data-driven models have been shown to be valuable approaches to enable fast water quality assessments....
journal article 2024
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Nastos Konstantopoulos, C. (author), Komninos, P. (author), Zarouchas, D. (author)
A hybrid methodology based on numerical and non-destructive experimental schemes, which is able to predict the structural level strength of composite laminates is proposed on the current work. The main objective is to predict the strength by substituting the up to failure experiments with non-destructive experiments where the investigated...
journal article 2023
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van Essen, S.M. (author), Seyffert, Harleigh C. (author)
Green water and slamming wave impacts can lead to severe damage or operability issues for marine structures. It is therefore essential to consider their probability and loads in design. This is difficult, as impacts are both hydrodynamically complex and relatively rare. The complexity requires high-fidelity modeling (experiments or CFD),...
journal article 2023
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Luijten, Ben (author), Ossenkoppele, B.W. (author), de Jong, N. (author), Verweij, M.D. (author), Eldar, Yonina C. (author), Mischi, Massimo (author), van Sloun, Ruud J.G. (author)
Ultrasound imaging is an attractive imaging modality due to its low-cost and real-time feedback, although it often falls short in image quality compared to MRI and CT imaging. Conventional ultrasound image reconstruction, such as Delay-and-Sum beamforming, is derived from maximum-likelihood estimation. As such, no prior information is exploited...
conference paper 2023
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Smirnova, Alisa (author), Yang, J. (author), Yang, Dingqi (author), Cudre-Mauroux, Philippe (author)
Noisy labels represent one of the key issues in supervised machine learning. Existing work for label noise reduction mainly takes a probabilistic approach that infers true labels from data distributions in low-level feature spaces. Such an approach is not only limited by its capability to learn high-quality data representations, but also by...
journal article 2022
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Hanea, Anca Maria (author), Nane, G.F. (author)
contribution to periodical 2022
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de Kok, Tim (author)
Implementation of nature-based solutions (NBS) in flood defenses is hindered by a lack of probabilistic tools and design guidelines that can be used to assess spatial and temporal variability in these biophysical systems. It is well established that nature-based elements, such as vegetation, attenuate waves, capture sediment, strengthen the...
master thesis 2021
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van den Bos, Niek (author)
The field of prognostics on composites is relatively young, and research is focused on constant amplitude fatigue (CAF) loading, whereas variable amplitude fatigue (VAF) loading is more common in actual use-cases. Therefore in this research, the feasibility of different in-situ, data-driven probabilistic models is studied for prognostics on...
master thesis 2020
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Sinke, Joël (author)
During the design phase of a foundation installation aspects are easily overlooked. When this aspect is overlooked a foundation element risks not reaching its design depth or getting damaged during the installation process. As a result significant delays and/or costs could occur. A driveability study gives insight in the installation aspects of...
master thesis 2020
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Zhang, Zixin (author)
This study aims to explore the possibility of employing remote sensing images to build a probabilistic flood extent forecasting model. This model is constructed and tested in two study areas: New Orleans and Miami. Images that recorded flooding events are first performed with segmentation method Seed Region Growing, and segmented images are...
master thesis 2020
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Paprotny, D. (author), Morales Napoles, O. (author), Worm, Daniël T.H. (author), Ragno, E. (author)
Bayesian Networks (BNs) are probabilistic, graphical models for representing complex dependency structures. They have many applications in science and engineering. Their particularly powerful variant – Non-Parametric BNs – are for the first time implemented as an open-access scriptable code, in the form of a MATLAB toolbox “BANSHEE”.<sup>1<...
journal article 2020
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Xu, L. (author), Zhai, Wan Ming (author)
To efficiently select track irregularity random samples for satisfying the ergodicity requirements of excitation sources in stochastic dynamics and reliability analysis in vehicle-track system, the weak-stationarity and similarity spectral of track irregularities were introduced to propose a track irregularity probabilistic model. Using the...
journal article 2018
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Oosterlo, P. (author), McCall, R.T. (author), Vuik, V. (author), Hofland, Bas (author), van der Meer, J.W. (author), Jonkman, Sebastiaan N. (author)
Shallow foreshores in front of coastal dikes can reduce the probability of dike failure due to wave overtopping. A probabilistic model framework is presented, which is capable of including complex hydrodynamics like infragravity waves, and morphological changes of a sandy foreshore during severe storms in the calculations of the probability of...
journal article 2018
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van Bekkum, Rob (author)
Decision-theoretic planning techniques are increasingly being used to obtain (optimal) plans for domains involving uncertainty, which may be present in the form of the controlling agent's actions, its percepts, or exogenous factors in the domain. These techniques build on detailed probabilistic models of the underlying system, for which Markov...
master thesis 2017
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Farah, H. (author), Azevedo, Carlos Lima (author)
The increased availability of detailed trajectory data sets from naturalistic, observational, and simulation-based studies, is a key source for potential improvements in the development of detailed safety models that explicitly account for vehicle conflict interactions and various driving maneuvers. Despite the well-recognized research...
journal article 2017
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Suh Heo, H.Y. (author)
Various flood protection measures are studied across the globe, and nature-friendly and environmentally resilient methods are gaining more attention. As part of the building with nature initiative, the project BE SAFE (Bio-Engineering for SAFEty) studies the effects of a vegetated foreshore as a flood protection measure which is found to be very...
master thesis 2016
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Verstegen, E. (author)
Conventional hydrological models use a deterministic approach. One could think of it like a black box, having an input, parameters, relations and an output. The parameters are calibrated by comparing the model output with observations of the system response (for example river runoff). When assessing the uncertainty in models the focus is often...
master thesis 2016
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Huibregtse, E. (author), Morales Napoles, O. (author), Hellebrandt, L. (author), Paprotny, D. (author), De Wit, S. (author)
This paper presents a risk-based method to quantify climate change effects on road infrastructure, as a support for decision-making on interventions. This can be implemented in climate adaptation plans as an element of asset management. The method is illustrated by a specific case in which traffic on a road network is disrupted by the flooding...
journal article 2016
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Ciftcioglu, O. (author), Bittermann, M.S. (author), Datta, R (author)
A robust probabilistic constraint handling approach in the framework of joint evolutionary-classical optimization has been presented earlier. In this work, the<br/>theoretical foundations of the method are presented in detail. The method is known as bi-objective method, where the conventional penalty function approach is implemented. The present...
conference paper 2016
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Bittermann, M.S. (author), Ciftcioglu, O. (author)
Demonstrative results of a probabilistic constraint handling approach that is exclusively using evolutionary computation are presented. In contrast to other works involving the same probabilistic considerations, in this study local search has been omitted, in order to assess the necessity of this deterministic local search procedure in...
conference paper 2016
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