document

The uncertainty associated with the use of copulas in multivariate analysis

Zhou, C. (author), van Nooijen, R.R.P. (author), Kolechkina, A.G. (author), Gargouri, E.F.G. (author), Slama, Fairouz (author), van de Giesen, N.C. (author)

The dependency structure between hydrological variables is of critical importance to hydrological modelling and forecasting. When a copula capturing that dependence is fitted to a sample, information on the uncertainty of the fit is needed for subsequent hydrological calculations and reasoning. A new method is proposed to report inferential...

journal article 2023

document

A Rigorous Analysis of the Random Noise in Reflection Coefficients Synthesized via Mixed-Signal Active Tuners

Mubarak, F.A. (author), Muñoz Muñoz, F.A. (author), Spirito, M. (author)

In this contribution, we present a rigorous analysis based on uncertainty propagation techniques to estimate the random variation of the controlled reflection coefficient in mixed-signal load-pull test benches. A digital-to-analog converter is commonly used in these test benches to generate the baseband signal required to synthesize the high...

conference paper 2023

document

A retrospective assessment of COVID-19 model performance in the USA

Colonna, Kyle J. (author), Nane, G.F. (author), Choma, Ernani F. (author), Cooke, R.M. (author), Evans, John S. (author)

Coronavirus disease 2019 (COVID-19) forecasts from over 100 models are readily available. However, little published information exists regarding the performance of their uncertainty estimates (i.e. probabilistic performance). To evaluate their probabilistic performance, we employ the classical model (CM), an established method typically used...

journal article 2022

document

Early observability of EOR process effectiveness

Fatemi, S.A. (author)

This dissertation focuses on polymer flooding, as an example of an EOR process. Chemical floods such as polymer floods are EOR techniques intended to increase sweep and/or displacement efficiency. Even though the compatibility and the efficiency of the injected chemicals are thoroughly tested and validated in the laboratory, uncertainty still...

doctoral thesis 2021

document

3D Ensemble Simulation of Seawater Temperature: An Application for Aquaculture Operations

Shettigar, Nithin Achutha (author), Bhattacharya, Biswa (author), Mészáros, L. (author), Spinosa, A. (author), El Serafy, G.Y.H. (author)

During the past decades, the aquaculture industry has developed rapidly, due to drop in wild fish catch. Water quality variables play major role in aquaculture operations, specifically seawater temperature has major impact on the metabolism of the fish species and therefore on the growth rate too. Since the fish farming business relies on the...

journal article 2020

document

Using Vine Copulas to Generate Representative System States for Machine Learning

Konstantelos, Ioannis (author), Sun, Mingyang (author), Tindemans, Simon H. (author), Issad, Samir (author), Panciatici, Patrick (author), Strbac, Goran (author)

The increasing uncertainty that surrounds electricity system operation renders security assessment a highly challenging task; the range of possible operating states expands, rendering traditional approaches based on heuristic practices and ad hoc analysis obsolete. In turn, machine learning can be used to construct surrogate models...

journal article 2019

document

Uncertainty Analysis of Phytoplankton Dynamics in Coastal Waters

Niu, L. (author)

There is an increasing concern about the interactions between phytoplankton and coastal ecosystems, especially on the negative effects from coastal eutrophication and phytoplankton blooms. As the key indicator of the coastal ecosystem, phytoplankton plays an important role in the whole impact-effect chain. Primary production by phytoplankton...

doctoral thesis 2015

document

The Copula Bayesian Network with mixed discrete and continuous nodes to forecast railway disruption lengths

Zilko, A.A. (author), Kurowicka, D. (author), Hanea, A.M. (author), Goverde, R.M.P. (author)

The highly uncertain nature of a railway disruption complicates the tasks carried by the Dutch Operational Control Centre Rail (OCCR) in the Netherlands. A good prediction of disruption length is believed to help the decision making in dealing with the disruption. Zilko, et al. [Non-Parametric Bayesian Network to Forecast Railway Disruption...

conference paper 2015

document

Helicopter-Ship Qualification Testing

Hoencamp, A. (author)

The goal of this research project is to develop a novel test methodology which can be used for optimizing cost and time efficiency of helicopter-ship qualification testing without reducing safety. For this purpose, the so-called “SHOL-X” test methodology has been established, which includes the associated predictive software tool as developed in...

doctoral thesis 2015

document

Refining the Committee Approach and Uncertainty Prediction in Hydrological Modelling

Kayastha, N. (author)

Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of models. One of multi modelling approaches called ...

doctoral thesis 2014

document

Prediction Of Hydrological Models’ Uncertainty By A Committee Of Machine Learning-Models

Kayastha, N. (author), Solomatine, D.P. (author), Lal Shrestha, D. (author)

In the MLUE method (reported in Shrestha et al. [1, 2]) we run a hydrological model M for multiple realizations of parameters vectors (Monte Carlo simulations), and use this data to build a machine learning model V to predict uncertainty (quantiles) of the model M output. In this paper, for model V, we employ three machine learning techniques,...

conference paper 2014

document

Probabilistic Analysis for Capacity Planning in Smart Grid at Residential Low Voltage Level by Monte-Carlo Method

Du, W. (author)

Smart Grid integrates sustainable energy sources and allows mutual communications between electricity distribution operators and electricity consumers. Electricity demand and supply becomes more complex in Smart Grid. It is more challenging for DNOs in grid asset capacity planning, especially at low voltage level. In this research, probabilistic...

journal article 2011

document

Control of Propeller Cavitation in Operational Conditions

Vrijdag, A. (author)

Off design conditions can have a severe impact on ship propulsion system behaviour. Resistance increase for instance leads to a higher engine loading, and can also easily lead to a decrease of cavitation inception speed with respect to calm water conditions. Wakefield variations due to ship motions, waves and manoeuvres also have effect on...

doctoral thesis 2009

document

Using copulas for modeling stochastic dependence in power system uncertainty analysis

Papaefthymiou, G. (author), Kurowicka, D. (author)

The increasing penetration of renewable generation in power systems necessitates the modeling of this stochastic system infeed in operation and planning studies. The system analysis leads to multivariate uncertainty analysis problems, involving non-Normal correlated random variables. In this context, the modeling of stochastic dependence is...

journal article 2009

document

A novel method to estimate model uncertainty using machine learning techniques

Solomatine, D.P. (author), Lal Shrestha, D. (author)

A novel method is presented for model uncertainty estimation using machine learning techniques and its application in rainfall runoff modeling. In this method, first, the probability distribution of the model error is estimated separately for different hydrological situations and second, the parameters characterizing this distribution are...

journal article 2009

document

Intertwining uncertainty analysis and decision-making about drinking water infrastructure

Meijer, H.M. (author)

Infrastructures, generally designed to have a long service life, are particularly vulnerable to long term changes that can influence their functioning. Therefore it is important that uncertainties are taken into account as much as possible from the beginning of the planning process of infrastructures. This thesis focuses on drinking water...

doctoral thesis 2007

document

Integration of stochastic generation in power systems

Papaefthymiou, G. (author)

Stochastic Generation is the electrical power production by the use of an uncontrollable prime energy mover, corresponding mainly to renewable energy sources. For the large-scale integration of stochastic generation in power systems, methods are necessary for the modeling of power generation uncertainty. In this thesis, new tools for the...

doctoral thesis 2007

document

Stochastic Flutter Analysis

Verhoosel, C.V. (author), Gutiérrez, M.A. (author), Hulshoff, S.J. (author)

The field of fluid-structure interaction is combined with the field of stochastics to perform a stochastic flutter analysis. Various methods to directly incorporate the effects of uncertainties in the flutter analysis are investigated. The panel problem with a supersonic fluid flowing over it is considered as a testcase. The stochastic moments ...

report 2006

document

Stochastic modelling of river morphodynamics

Van Vuren, B.G. (author)

Modern river management has to reconcile a number of functions, such as protection against floods and provision of safe and efficient navigation, floodplain agriculture, ecology and recreation. Knowledge on uncertainty in fluvial processes is important to make this possible, to design effective river engineering works, for operational...

doctoral thesis 2005

document

The interaction between diesel engines, ship and propellers during manoeuvring

Schulten, P.J.M. (author)

doctoral thesis 2005