Work Package 6

Applying machine learning methods to better understand, model and estimate mass concentrations of traffic-related pollutants at a typical street canyon

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Narrow city streets surrounded by tall buildings are favorable to inducing a general effect of a “canyon” in which pollutants strongly accumulate in a relatively small area because of weak or inexistent ventilation. In this study, levels of nitrogen-oxide (NO2), elemental carbon (EC) and organic carbon (OC) mass concentrations in PM10 particles were determined to compare between seasons and different years. Daily samples were collected at one such street canyon location in the center of Zagreb in 2011, 2012 and 2013.

Jan Velimsky, Christoph Schweimer, Christine Gfrerer

Message spread on Social Media. Comparing the FPÖ and NEOS during the election campaign of the 2019 Austrian National Council Elections

Synthesizing Infomap – A Kullback-Leibler Divergence-Based Approach To Community Detection

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Community detection is an essential tool for analyzing the organization of complex social, biological and information networks. Among the numerous community detection algorithms proposed so far, Infomap is a prominent and well-established framework. In this thesis, we propose a novel method for community detection inspired by Infomap.

AI-Support for large-scale refugee movement simulations

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Model (Order) Reduction

By Mark Kröll on Fri, 03/27/2020 - 14:02

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Techniques to reduce the (computational) complexity of a high dimensional system/model/object to a lower dimensional system/model/object (without losing a significant amount of accuracy)

Machine Learning

By Mark Kröll on Fri, 03/27/2020 - 14:00

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Machine Learning is an application of Artificial Intelligence that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed. It focuses on the development of computer programs that can access data and use it to learn from it. There are several types of ML, e.g.