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Schuurman, Kevin (author)The use of deep learning in global weather forecasting has shown significant promise in improving both forecasting accuracy and speed. Traditional numerical weather prediction models have gradually improved forecasting skills but at the cost of increased computational complexity. In contrast, new deep learning models, trained directly on...master thesis 2023
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- Dijkstra, Bart (author) master thesis 2023
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Wang, Heqi (author)Accurate and trustworthy short-term traffic prediction is crucial in the modern world for the comfort of drivers and decision-makers as it is used to improve the performance of traffic management systems, lessen congestion, increase safety, and shorten journey times. It is possible to discover useful information for network transportation...master thesis 2023
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Bayraktar, Kerem (author)The term ”Algal Bloom” refers to the accumulation of algae in a confined geological space. They may harm human health and negatively affect ecological systems around the area. Thus, forecasting algal blooms could mitigate the environmental and socio-economical damages. Particularly, the use of deep learning methods could distinguish underlying...bachelor thesis 2023
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Lubbers, Rob (author)The aim of this paper is to find out which Machine Learning (ML) model predicts the concentration of Chlorophyll-a, in the Palmar lake in Uruguay best. Currently there are no such models to predict the growth in this lake. The algorithms which will be compared in this paper are a Linear Regression model and the U-Net model. We will compare the...bachelor thesis 2023
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de Gruyl, Einar (author)This research presents a method for forecasting algal blooms using remote sensing with spatially and temporally sparse satellite data. The method involves the use of multiple interpolation methods to interpolate the sparse input data. The approach is shown to be effective in predicting algal blooms in areas where data is sparse, and the results...bachelor thesis 2023
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Mao, Kangmin (author)Modeling the relationship between rainfall and runoff is a longstanding challenge in hydrology and is crucial for informed water management decisions. Recently, Deep Learning models, particularly Long short-term memory (LSTM), have shown promising results in simulating this relationship. The Transformer, a newly proposed deep learning...master thesis 2023
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de Boer, Jens (author)A significant decrease in greenhouse gas emissions can be achieved by including a prediction of future power consumption in the control of ships’ power plants during transits. Moreover, including a prediction of power consumption in the Energy Management System (EMS) during Dynamic Positioning (DP) operations can also contribute to a reduction...master thesis 2023
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Grzebyk, Daniel (author), Alcañiz Moya, A. (author), Donker, Jaap (author), Zeman, M. (author), Ziar, H. (author), Isabella, O. (author)Due to the inherent uncertainty in photovoltaic (PV) energy generation, an accurate power forecasting is essential to ensure a reliable operation of PV systems and a safe electric grid. Machine learning (ML) techniques have gained popularity on the development of this task due to its increased accuracy. Most literature, however, focuses only...journal article 2023
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Muñoz, Paul (author), Corzo, Gerald (author), Solomatine, D.P. (author), Feyen, Jan (author), Célleri, Rolando (author)Extreme peak runoff forecasting is still a challenge in hydrology. In fact, the use of traditional physically-based models is limited by the lack of sufficient data and the complexity of the inner hydrological processes. Here, we employ a Machine Learning technique, the Random Forest (RF) together with a combination of Feature Engineering (FE...journal article 2023
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Oskina, M.I. (author), Farah, H. (author), Morsink, Peter (author), Happee, R. (author), van Arem, B. (author)The operation of automated vehicles (AVs) on shared roads requires attention concerning their interactions with vulnerable road users (VRUs), such as cyclists. This study investigates the safety of cyclists when they interact with an AV and compares it with their interaction with a conventional vehicle. Overall, 29 cyclists participated in a...journal article 2023
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Rahmani, S. (author), Baghbani, Asiye (author), Bouguila, Nizar (author), Patterson, Zachary (author)Graph neural networks (GNNs) have been extensively used in a wide variety of domains in recent years. Owing to their power in analyzing graph-structured data, they have become broadly popular in intelligent transportation systems (ITS) applications as well. Despite their widespread applications in different transportation domains, there is no...journal article 2023
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de Bekker, Philippe (author), Cremers, S.A. (author), Norbu, Sonam (author), Flynn, David (author), Robu, Valentin (author)Given the fundamental role of renewable energy assets in achieving global temperature control targets, new energy management methods are required to efficiently match intermittent renewable generation and demand. Based on analysing various designed cases, this paper explores a number of heuristics for a smart battery scheduling algorithm that...journal article 2023
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van der Werf, J.A. (author), Kapelan, Z. (author), Langeveld, J.G. (author)Urban Drainage Systems can cause ecological and public health issues by releasing untreated contaminated water into the environment. Real-time control (RTC), augmented with rainfall nowcast, can effectively reduce these pollution loads. This research aims to identify key dynamics in the nowcast accuracies and relate those to the performance...journal article 2023
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Raman, C.A. (author), Hung, H.S. (author), Loog, M. (author)Free-standing social conversations constitute a yet underexplored setting for human behavior forecasting. While the task of predicting pedestrian trajectories has received much recent attention, an intrinsic difference between these settings is how groups form and disband. Evidence from social psychology suggests that group members in a...conference paper 2023
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Vo, Tung (author), Barbour, N.M. (author), Palaio, Lori (author), Maness, Michael (author)Bikesharing is a popular transportation mode for people to commute, for leisurely travel, or for recreation purposes in their daily tasks. Throughout 2020, the COVID-19 pandemic had significant impacts on bikeshare usage in the United States. Previous studies show that the pandemic negatively affected bikeshare activity patterns. To examine the...book chapter 2023
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LIU, JIshan (author)SITA is the world’s leading specialist in air transport communications and information technology which works with around 400 air transport members and has 2800 customers in 190 countries. TS6 kiosk is the newest generation of its kiosk family and is facing a complicated situation now. Usually, the production of a kiosk is using make-to-order...master thesis 2022
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Krabbenborg, Britt (author)Banks such as Rabobank depend on multi-year mortgage prepayment forecasts in order to make provisions for the associated prepayment risks. The econometric models they use are fitted to historical data, and as a consequence their models are fitted to a decreasing interest rate regime. Given the current economic climate of increasing interest...master thesis 2022
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Zwart, Lotte (author)Whereas in the past, the Distribution System Operator (DSO) almost never encountered congestion in their grids, nowadays, with the increase of connected renewable energy sources, this will become more prevalent. To forecast congestion on transformer stations, with the goal of mitigating it, the Dutch DSO Stedin uses machine learning models with...master thesis 2022
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Hoogeveen, Sylle (author)The increase in complexity of mathematical models in an attempt to approximate reality and desire to have near real-time results have emphasized the need for fast numerical simulations. Especially in areas where classic numerical methods struggle to produce valid solutions in reasonable computational time due to their<br/>complex behaviour on...master thesis 2022