Searched for: subject%3A%22Forecasting%22
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Revilla Llaca, Rodrigo (author)
Accurate forecasts are essential for integrating wind energy into the power grid. With wind energy's growing role in the renewable mix, precise short-term generation forecasts are increasingly vital. Turbine-level forecasts are critical for optimal wind farm operation, control, and planning. However, the wind's unpredictability and the complex...
master thesis 2024
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Diab Montero, H.A. (author)
In this dissertation, I explore ensemble data assimilation methods to enhance our capability to forecast earthquakes and slow slip events, focusing on the critical challenge posed by limited information on the current stress state of faults. <br/>At the outset, the research acknowledges the inherent limitations in our current understanding of...
doctoral thesis 2024
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Sara Boby, Sara (author)
In the field of fluid mechanics, there has been a significant shift towards the integration of machine and deep learning techniques to address challenges in reduced-order modeling, flow feature analysis, and control, especially within the realm of active flow control (AFC) for objectives such as lift optimization and drag reduction. Deep...
master thesis 2024
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Sarkisian, David (author)
This thesis explores how forecasts of Dutch government bond yields can be improved by extending the current Dynamic Nelson-Siegel (DNS) model, used by the Dutch State Treasury Agency (DSTA), with stochastic volatility modeling and a Bayesian approach to parameter estimation and forecasting. The primary goal was to determine if the model...
master thesis 2024
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Katona, Misha (author)
Through several contractions, stiff competition, and increasing passenger expectations, airports must evolve continually. One of the main avenues for this has been improving the efficiency of the security check- points, which are airports’ primary bottlenecks. Operational optimisation methods, such as resource and task scheduling are relatively...
master thesis 2024
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Li, G. (author), Knoop, V.L. (author), van Lint, J.W.C. (author)
Traffic condition forecasting is fundamental for Intelligent Transportation Systems. Besides accuracy, many services require an estimate of uncertainty for each prediction. Uncertainty quantification must consider the inherent randomness in traffic dynamics, the so-called aleatoric uncertainty, and the additional distrust caused by data shortage...
journal article 2024
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Marsman, C. P. (author), Vossepoel, F.C. (author), Van Dinther, Y. (author), Govers, R. (author)
Bayesian-based data assimilation methods integrate observational data into geophysical forward models to obtain the temporal evolution of an improved state vector, including its uncertainties. We explore the potential of a variant, a particle method, to estimate mechanical parameters of the overriding plate during the interseismic period....
journal article 2024
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Mateo-Barcos, S. (author), Ribo-Perez, D.G. (author), Rodríguez-García, J. (author), Alcázar-Ortega, M. (author)
This study develops a methodology to characterise and forecast large consumers’ electricity demand, particularly municipalities, with hundreds of different metered supply points based on the previous characterisation of facilities’ consumption. Demand forecasting allows consumers to improve their participation in electricity markets and...
journal article 2024
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Sadrtdinova, Renata (author), Perez, Gerald Augusto Corzo (author), Solomatine, D.P. (author)
Kazakhstan is recently experiencing an increase in drought trends. However, low-capacity probabilistic drought forecasts and poor dissemination have led to a drought crisis in 2021 that resulted in the loss of thousands of livestock. To improve drought forecasting accuracy, this study applies Machine Learning and Deep Learning (ML and DL)...
journal article 2024
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van der Drift, R. (author), de Haan, J. (author), Boelhouwer, P.J. (author)
As housing development and housing market policies involve many long-term decisions, improving house price predictions could benefit the functioning of the housing market. Therefore, in this paper, we investigate how house price predictions can be improved. In particular, the merits of Bayesian estimation techniques in enhancing house price...
journal article 2024
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Wang, X. (author), Corzo, Gerald (author), Lü, Haishen (author), Zhou, Shiliang (author), Mao, K. (author), Zhu, Yonghua (author), Duarte Prieto, F.S. (author), Liu, Mingwen (author), Su, Jianbin (author)
Sub-seasonal drought forecasting is crucial for early warning in estimating agricultural production and optimizing irrigation management, as forecasting skills are relatively weak during this period. Soil moisture exhibits stronger persistence compared to other climate system quantities, which makes it especially influential in shaping land...
journal article 2024
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Raja, A.A. (author), Pinson, Pierre (author), Kazempour, Jalal (author), Grammatico, S. (author)
In many areas of industry and society, including energy, healthcare, and logistics, agents collect vast amounts of data that are deemed proprietary. These data owners extract predictive information of varying quality and relevance from data depending on quantity, inherent information content, and their own technical expertise. Aggregating...
journal article 2024
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Diab Montero, H.A. (author), Størksen Stordal, Andreas (author), van Leeuwen, Peter Jan (author), Vossepoel, F.C. (author)
Probabilistic forecasts are regarded as the highest achievable goal when predicting earthquakes, but limited information on stress, strength, and governing parameters of the seismogenic sources affects their accuracy. Ensemble data-assimilation methods, such as the Ensemble Kalman Filter (EnKF), estimate these variables by combining physics...
working paper 2024
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Ma, L. (author), Qiu, Z. (author), Van Mieghem, P.F.A. (author), Kitsak, M.A. (author)
Epidemic forecasts are only as good as the accuracy of epidemic measurements. Is epidemic data, particularly COVID-19 epidemic data, clean, and devoid of noise? The complexity and variability inherent in data collection and reporting suggest otherwise. While we cannot evaluate the integrity of the COVID-19 epidemic data in a holistic fashion, we...
journal article 2024
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Hartgring, Sebastian (author)
The Netherlands, Germany, and Belgium were hit by heavy and prolonged precipitation in July 2021. As time passed, weather warnings escalated, leading to evacuations due to predicted floods, including in the Rur catchment. It was difficult to forecast the flooding of the Rur, raising the question of which elements are crucial in a flood...
master thesis 2023
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Beltman, Maarten (author)
Punctuality is a key performance indicator for any airline. Hub-and-spoke airlines are particularly committed to on-time arrivals to guarantee passenger connections. Flights that are delayed at departure need to compensate for the lost time whilst airborne. Because fueling takes place well before scheduled departure, predicted departure delays...
master thesis 2023
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Pauliks, Nils (author)
Purpose: This paper explores the potential of machine learning (ML) algorithms to mitigate uncertainty in early environmental assessments (ex-ante LCA), which are hindered by prospective nature and limited quantitative data availability. Methods: A systematic literature review with keyword searches on Scopus identified three ML categorization...
master thesis 2023
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Vos, Reinier (author)
Air traffic sector demand and capacity balancing is an important process to enable safe and efficient flight execution. In current operations, demand and capacity are determined based on schedules and flight plans. In reality, disruptions to flights create a different situation that may not have been anticipated by the Air Navigation Service...
master thesis 2023
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de Snoo, Ilian (author)
The Wadden Sea serves multiple roles: it acts as a protective barrier against severe wave conditions, is a natural habitat for diverse flora and fauna and has recreational purposes. This research provides a comprehensive analysis of the intricate morphological dynamics of the Wadden Sea. By implementing various model schematizations, the study...
master thesis 2023
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Deivamani, Karthikeyan (author)
The increasing adoption of renewable energy sources, particularly photovoltaic (PV) systems in residential sectors has raised important energy balancing challenges due to the intermittent nature of energy generation. To address these challenges and prioritize cost savings for residential consumers, this research investigates the integration of...
master thesis 2023
Searched for: subject%3A%22Forecasting%22
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