Development of a framework to estimate the condition of mechanical, electrical and plumbing systems with Bayesian Networks

As the Western European building stock ages, attention is increasingly allocated to the maintenance of building components, particularly mechanical, electrical and plumbing (MEP) systems. Although the latter are essential in ensuring the correct operation of a building and the safety of its occupants, they remain the crafts where the most...

Sequential decision making using Bayesian networks and reinforcement learning: to determine the hydrocarbon prospect exploration strategy

In the process of drilling wells to produce hydrocarbons, an exploration strategy is used to determine which wells should be drilled and in which order. This strategy is vital, as a suboptimal drilling sequence will lead to more expenses and fewer gains.<br/>Furthermore, the wells considered in most exploration strategies are geologically<br/...

Decision Making under Uncertainty for Automated Vehicles in Urban Situations

One of the most crucial links to building an autonomous system is the task of decision making. The ability of a vehicle to make robust decisions on its own by predicting and assessing future consequences is what makes it intelligent. This task of decision making becomes even more complex due to the fact that the real world is uncertain,...

Modelling citation performance of Canadian researchers using Bayesian Networks

This thesis is about modelling citation performance using Bayesian networks (BN). As an approximation for citation performance, we will use the proportion of papers by an author that resulted in being one of the top 10% most cited papers. Using 15 predicting variables such as year of first publication and average number of authors per paper, we...

Bayesian networks in performance of cyclists

This report examines the possibility of modeling the performance of professional cyclists of Team Sunweb using Bayesian Networks. This research has an objective to see how these structures work and how they fit in the complex world of cycling. We want to compare different cyclists of Team Sunweb in the Grand Tours (Giro d'Italia, Tour de France...

Constructing non-parametric Bayesian networks from data

The objective of this thesis is to design an algorithm for learning the structure of non-parametric Bayesian networks (BNs) from data and has been written as part of acquiring the bachelor's degree at the Delft Institute of Applied Mathematics of the TU Delft. Inspiration for improving an existing algorithm while designing a new procedure was...