Searched for: subject%3A%22artificial%255C%2Bneural%255C%2Bnetworks%22
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Römer, Stijn (author)
Recent developments in \ac{ML} have paved the way for unprecedented possibilities in the field of data analytics in numerous team sports, such as American football, baseball, and basketball. In more recent years, \ac{ML} techniques have been applied to football as professional teams got inspired to collect enormous quantities of data to evaluate...
master thesis 2022
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Bajaj, V. (author), Buchali, Fred (author), Chagnon, Mathieu (author), Wahls, S. (author), Aref, Vahid (author)
High-symbol-rate coherent optical transceivers suffer more from the critical responses of transceiver components at high frequency, especially when applying a higher order modulation format. Recently, we proposed in [20] a neural network (NN)-based digital pre-distortion (DPD) technique trained to mitigate the transceiver response of a 128...
journal article 2022
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Janssens, M. (author), Hulshoff, S.J. (author)
Data-driven parameterizations offer considerable potential for improving the fidelity of General Circulation Models. However, ensuring that these remain consistent with the governing equations while still producing stable simulations remains a challenge. In this paper, we propose a combined Variational-Multiscale (VMS) Artificial Neural...
journal article 2022
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Sun, B. (author), Wang, Xuerui (author), van Kampen, E. (author)
In this paper, we establish an event-triggered intelligent control scheme with a single critic network, to cope with the optimal stabilization problem of nonlinear aeroelastic systems. The main contribution lies in the design of a novel triggering condition with input constraints, avoiding the Lipschitz assumption on the inverse hyperbolic...
journal article 2022
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Cuperman, Rafael (author), Jansen, K.M.B. (author), Ciszewski, M.G. (author)
Action statistics in sports, such as the number of sprints and jumps, along with the details of the corresponding locomotor actions, are of high interest to coaches and players, as well as medical staff. Current video-based systems have the disadvantage that they are costly and not easily transportable to new locations. In this study, we...
journal article 2022
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Liu, S. (author), Grzelak, L.A. (author), Oosterlee, C.W. (author)
We propose an accurate data-driven numerical scheme to solve stochastic differential equations (SDEs), by taking large time steps. The SDE discretization is built up by means of the polynomial chaos expansion method, on the basis of accurately determined stochastic collocation (SC) points. By employing an artificial neural network to learn these...
journal article 2022
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Teo, Ying Shen (author), Jafari, Iman (author), Liang, Fei (author), Jung, Youmi (author), van der Hoek, J.P. (author), Ong, Say Leong (author), Hu, Jiangyong (author)
The UV/Cl2 process (also known as chlorine photolysis, which is the combination of chlorine and simultaneous irradiation of UV light) is conventionally applied at acidic mediums for drinking water treatment and further treatment of wastewater effluents for secondary reuse. This is because the quantum yield of HO• from HOCl (ϕHO•, 254 = 1.4) is...
journal article 2022
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Overwater, R.W.J. (author), Babaie, M. (author), Sebastiano, F. (author)
Quantum error correction (QEC) is required in quantum computers to mitigate the effect of errors on physical qubits. When adopting a QEC scheme based on surface codes, error decoding is the most computationally expensive task in the classical electronic back-end. Decoders employing neural networks (NN) are well-suited for this task but their...
journal article 2022
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Rosin, T. R. (author), Kapelan, Z. (author), Keedwell, E. (author), Romano, M. (author)
Blockages are a major issue for wastewater utilities around the world, causing loss of service, environmental pollution, and significant cleanup costs. Increasing telemetry in combined sewer overflows (CSOs) provides the opportunity for near real-time data-driven modelling of wastewater networks. This paper presents a novel methodology,...
journal article 2022
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Köylü, T.C. (author), Hamdioui, S. (author), Taouil, M. (author)
Artificial neural networks (ANNs) are used to accomplish a variety of tasks, including safety critical ones. Hence, it is important to protect them against faults that can influence decisions during operation. In this paper, we propose smart and low-cost redundancy schemes that protect the most vulnerable ANN parts against fault attacks....
conference paper 2022
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Verma, Ayush (author)
With growing wind energy capacity, especially offshore, reliability of wind turbines (WT) becomes a relevant concern. Poor reliability directly affects their cost effectiveness due to increased operation and maintenance ...
master thesis 2021
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Jeken Rico, P. (author)
The following project deals with the optimization of simulation parameters such as the injection location and pitch angle of polyurethane foaming simulations using artificial neural networks. The model's target is to predict quality variables based on the process parameters and the geometry features. Through several evaluations of the model,...
master thesis 2021
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Cuperman Coifman, Rafael (author)
been given to Human Activity Recognition (HAR) based on signals obtained by IMUs placed on different body parts. This thesis studies the usage of Deep Learning-based models to recognize different football activities in an accurate, robust, and fast manner. Several deep architectures were trained with data captured with IMU sensors placed on...
master thesis 2021
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Van Santvliet, Pieter (author), Rozendaal, Aart (author)
This thesis shows the detailed design of the control and software of a DC microgrid of a tiny house community on the roof of a high-rise building in the city of Rotterdam in the Netherlands, consisting of twelve tiny houses powered by solar and wind energy. This thesis is part of a project with two other subgroups, focusing on the microgrid...
bachelor thesis 2021
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Saz Ulibarrena, Veronica (author)
The use of low-thrust propulsion for interplanetary missions requires the implementation of new methods for the preliminary design of their trajectories. This thesis proposes a method using the Monotonic Basin Hopping global optimization algorithm to find feasible trajectories with optimum use of the mass of fuel for the case in which the...
master thesis 2021
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van der Woude, Mark (author)
Widespread usage of Micro Aerial Vehicles (MAVs) has led to various airspace safety breaches, including near mid-air collisions with other aircraft. To ensure safe integration into general aviation, it is paramount that MAVs are equipped with an autonomous detect and avoid system when flying beyond the visual line-of-sight of the operator. The...
master thesis 2021
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van den Haak, Daniel (author)
Lane change decision-making is an important challenge for automated vehicles, urging the need for high performance algorithms that are able to handle complex traffic situations. Deep reinforcement learning (DRL), a machine learning method based on artificial neural networks, has recently become a popular choice for modelling the lane change...
master thesis 2021
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Becker, Midas (author)
<br/>Being a safe and healthy alternative for polluting and space-inefficient motorised vehicles, cycling can strongly improve living conditions in urban areas. Idling in front of traffic lights is seen as one of the major inconveniences of commuting by bicycle. By giving personalised speed advice, the probability of catching a green light can...
master thesis 2021
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Brederveld, J.E.C. (author)
Various machine learning algorithms have been applied to find optimal lowthrust<br/>satellite trajectories, however, no fair comparison of their accuracy has been made yet. In this paper, two common and promising supervised machine learning algorithms are compared for their regression capacities:<br/>the artificial neural network and the...
master thesis 2021
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Nadi Najafabadi, A. (author), Sharma, Salil (author), Snelder, M. (author), Bakri, Taoufik (author), van Lint, J.W.C. (author), Tavasszy, Lorant (author)
Short-term traffic prediction is an important component of traffic management systems. Around logistics hubs such as seaports, truck flows can have a major impact on the surrounding motorways. Hence, their prediction is important to help manage traffic operations. However, The link between short-term dynamics of logistics activities and the...
journal article 2021
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