Searched for: subject%3A%22time%255C-series%22
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Verhagen, Alexandra (author)
Accurate capacity planning is essential to ensure uninterrupted services and network stability through peak hours for the transport core network of KPN. This involves a trade-off between minimizing the risks of capacity shortages and costs of capacity expansions. High network loads are occurring more frequently and their magnitude is increasing....
master thesis 2024
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van der Kraan, Frenk (author)
Gaining insights into anticipated future expenses is essential for both the planning and construction phases of a project. A significant factor in future costs, particularly over extended periods, is the variability of material and labor prices. the change in costs over time, known as ’cost escalation,’ has been the focus of numerous research...
master thesis 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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Alers, Tim (author)
The visibility graph has gained traction as a method for time series analysis. Through this method, it is possible to detect or quantify non-linear behavior in a myriad of fields and applications. This thesis explores the variations of visibility graphs, describes how they are used in literature and investigates what lies at the foundation of...
master thesis 2023
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Six, Kobi (author)
The aviation industry's reliance on automation raises concerns about pilot complacency, necessitating continuous pilot proficiency measures. To that end, real-time pilot skill feedback is vital—through alerts on declining skill levels or scalable levels of autonomy. Current cybernetic methods are limited as they assume linearity and time...
master thesis 2023
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Marramiero, Daniela (author)
Considering the goals set by the international community, the implementation of new energy sources has to increase considerably in the next seven years. In this thesis, the focus is on the acceleration and improvement of the application of offshore wind turbines. The power produced using this technology should become 3.6 times more before the...
master thesis 2023
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Shankar, Aditya (author)
Vertical federated learning’s (VFL) immense potential for time series forecasting in industrial applications such as predictive maintenance and machine control remains untapped. Critical challenges to be addressed in the manufacturing industry include small and noisy datasets, model explainability, and stringent privacy requirements for training...
master thesis 2023
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Kielhöfer, Marius (author)
The ability to accurately forecast sales volumes holds substantial significance for businesses. Current classical models struggle in capturing the impact of different variables upon the sales volume. These machine learning models are also not applicable to more than one specific product. The Temporal Fusion Transformer (TFT) is implemented to...
bachelor thesis 2023
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Herrmann, Lars (author)
As the volume of telemetry data generated by satellites and other complex systems continues to grow, there is a pressing need for more efficient and accurate anomaly detection methods. Current techniques often rely on human analysis and preset criteria, presenting several challenges including the necessity for expert interpretation and continual...
master thesis 2023
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de Beer, Arne (author)
This paper presents a study focused on developing an efficient signal processing pipeline and identifying suitable machine learning models for real-time gesture recognition using a testbed consisting of an Arduino Nano 33 BLE and three OPT101 photodiodes. Our research aims to address the challenges of limited computational power whilst...
bachelor thesis 2023
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Tung, Yu (author)
The study of energy consumption across various building clusters offers a path to discerning intricate patterns and establishing energy efficiency metrics. However, these analyses have mostly been limited to small, controlled settings, leaving a vast potential for broader application in energy efficiency management and classification untapped....
master thesis 2023
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Chiriţă, Matei (author)
The aim of this paper is to complete the gap in the knowledge and experiment using as little as only the heart rate of some subjects to manage to successfully authorise them in some supposed system. The focus will be on the Gaussian Mixture model and the One Class Support Vector Machine, both outlier detectors, because most of the past research...
bachelor thesis 2023
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Üzel, Ziyar (author)
Accurate short-term traffic forecasting plays a crucial role in Intelligent Transportation Systems for effective traffic management and planning. In this study, the performances of three popular forecasting models are explored: Long Short-Term Memory (LSTM), Autoregressive Integrated Moving Average (ARIMA), and Facebook's Prophet, for short-term...
bachelor thesis 2023
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Kienhuis, Maurits (author)
The ever-evolving power grid is becoming smarter and smarter. Modern houses come with smart meters and energy conscious consumers will buy additional smart meters to place in their home to help monitor their energy consumption. This new smart technology also opens the door to more accurate power consumption forecasting. In this study we look at...
bachelor thesis 2023
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Blanken, Emma (author)
Fire both shapes and destroys forests. Forest fires are therefore essential to ecological processes and vegetation as we know them. With climate change, forest fires are expected to increase in severity and frequency. To maintain the functioning of the forests, it is important to understand the vegetation response to and recovery from forest...
master thesis 2023
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Sui, Zhongyi (author), Wen, Yuanqiao (author), Huang, Yamin (author), Song, R. (author), Piera, Miquel Angel (author)
The theoretical analysis of maritime accidents is a hot topic, but the time characteristics and dynamics of maritime accidents time series are still unclear. It is difficult to draw a clear conclusion from the cause analysis, so the accident is difficult to be predicted. To bridge this gap, this research analyzes the characteristics and...
journal article 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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Draisma, Max (author)
Understanding the factors that drive extreme water levels is key to an accurate assessment of flood hazard. The city of Venice has always been affected by flooding due to extreme water levels. In this study, we examine the factors driving and influencing extreme water levels in the Venice lagoon, aiming at deriving accurate extreme water level...
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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Kartal, S. (author)
Spatiotemporal time series prediction plays a crucial role in a wide range of applications. However, in most of the studies, spatial information was ignored and predictions were carried out either on a few points or on average values. In this study, 37 different configurations of 4 traditional ML models and 3 Neural Network (NN) based models...
journal article 2023
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