document

Hybrid human-centric haptic shared control using artificial neural network and model predictive control

Harmankaya, Hüseyin (author)

Commercially available Lane Keeping Assist systems fail to consider the driver's intentions since they mainly focus on minimising path tracking errors, resulting in conflicts between humans and automation. This often leads to users being unsatisfactory and turning off the assist, as a result diminishing the advantages such as reduced workload...

master thesis 2023

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Microphones as Airspeed Sensors for Micro Air Vehicles

Makaveev, Momchil (author)

This project proposes and evaluates a novel concept for an airspeed instrument aimed at small hybrid unmanned aerial vehicles. The working principle is to relate the power spectra of the wall-pressure fluctuations beneath the turbulent boundary layer formed over the vehicle’s body to its airspeed. The instrument consists of two microphones,...

master thesis 2023

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Crashworthiness Analysis of An Aircraft Subfloor Structure using Artificial Neural Networks

Waaijer, Joost (author)

The goal of this thesis is to build an artificial neural network(ANN) surrogate model, that predicts the crashworthiness performance of a structure. The structure used in this research is a thermoplastic fibre-reinforced composite aircraft subfloor section which is part of the SmarT multifUNctioNal and INteGrated thermoplastic fuselage (STUNNING...

master thesis 2022

document

Trajectory Pruning with Neural Networks for Efficient Monte-Carlo based Quadrotor Flight Envelope Prediction

Kaneko, Kei (author)

Flight envelope prediction is a challenging task where one of the difficulties is that widely used methods, like the level set methods, are impractical for systems with more than four coupled state dimensions due to the “curse of dimensionality”. Monte-Carlo simulation based approach suffers less from this, however a large number of simulations...

master thesis 2022

document

An Artificial Neural Network Approach to Within-Game Predictions in Football using Spatiotemporal Data

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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Neural Network-based Optimization of Solid-and Fluid Mechanical Simulations

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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Wind turbine gearbox fault prognosis using high-frequency monitoring SCADA data

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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Football activity recognition: A deep learning approach to football activity recognition based on Inertial Measurement Units signals

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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Control & Software: Distribution of the electricity grid of a tiny house community

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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Low-Thrust Interplanetary Trajectory Optimization Using Pre-Trained Artificial Neural Network Surrogates

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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Acoustic-Based Aircraft Detection and Ego-Noise Suppression: for Micro Aerial Vehicles

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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Automated lane changing using deep reinforcement learning: a user-acceptance case study

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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Practical implementation of reinforcement learning algorithms for giving personalised speed advice to cyclists approaching intersections using function approximation and Dyna

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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Comparing the performance of machine learning methods in a surrogate approach to optimize low-thrust interplanetary trajectories

Brederveld, Jan (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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Artificial Intelligence-Based Radio Resource Management in Sliced Radio Access Networks

Arora, Apoorva (author)

In this thesis, we design and assess a multi-slice resource allocation framework that is based on machine learning techniques (subset of artificial intelligence techniques). The proposed framework employs two machine learning techniques namely, artificial neural networks and reinforcement learning for resource management in sliced RAN....

master thesis 2020

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Evaluation of linear regression and neural network methods for estimating occupancy in office buildings using bGrid sensor data

Kraaijeveld, Jelmer (author)

This thesis outlines the use of measured data collected using the bGrid system to estimate the number of people in two rooms in the Microsoft office at Schiphol. The main objective is to derive a correlation that transforms the data into a specific number of people. The bGrid system consists of a network of sensor nodes that measure CO2...

master thesis 2020

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Accelerating Basecalling with Dataflow Computing

Vermond, Lukas (author)

In an effort to make DNA sequencing more accessible and affordable, Oxford Nanopore Technologies developed the MinION: A portable cellphone sized DNA sequencing device. Translating the information from this device to a nucleotide sequence is called basecalling, and is done with the aid of artificial neural networks. In this thesis, we accelerate...

master thesis 2020

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European option pricing under the rough Heston model using the COS method

Erkan, K.E. (author)

This thesis is about pricing European options using a Fourier-based numerical method called the COS method under the rough Heston model. Besides examining the efficiency and accuracy of the COS method for pricing options under the rough Heston model, it is also investigated if the rough Heston model produces the advantages of the so-called rough...

master thesis 2020

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Humble Giants: Computational Intelligence for Designing More Sustainable High-rise Buildings using Surrogate Models

Fortich Mora, Fredy (author)

As urbanization increases around the world, high-rise buildings will continue to become a more prevailing typology, nonetheless, due in part to cumbersome computational simulations, rarely do designers have enough information during the early stages of design, which is the time when their choices affect the most the efficiency of their building....

master thesis 2020

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Noise-augmented offline training of ANN unresolved-scale models

Pusuluri, Abhinand (author)

An effective way to solve the forced Burgers' equation in a variational multiscale framework is to close the system of equations using unresolved-scale interaction terms predicted by an artificial neural network. The goal of this thesis is to investigate the accuracy and stability of the said system by training a neural network offline with data...

master thesis 2020