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Janssens, Martin (author)
Today's leading projections of climate change predicate on Atmospheric General Circulation Models (GCMs). Since the atmosphere consists of a staggering range of scales that impact global trends, but computational constraints prevent many of these scales from being directly represented in numerical simulations, GCMs require "parameterisations'' -...
master thesis 2019
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Vellekoop, E.C. (author)
master thesis 2016
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Nguyen, Tuan Anh (author)
Billions of wireless devices are interconnected to provide services to many<br/>aspects of life and form The Internet of Things. These devices which are<br/>often battery-powered and energy efficient can benefit greatly from an ac-<br/>curate localisation service that does not consume extra energy. Several loc-<br/>alisation methods have been...
master thesis 2019
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Terleth, Niels (author)
Due to their powerful approximation capabilities, artificial neural networks have seen a wide interest in various fields. A particular application is the use of an artificial neural network to predict solutions of the governing equations for fluid flow i.e. the Navier-Stokes equations. This is done by taking the space and time variables as the...
master thesis 2019
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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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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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