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Credit: Debra Larson, The Grainger College of Engineering
Over the past 20 years, the number of passengers traveling on British train networks has almost doubled to 1.7 billion annually. With numbers like that it s clear how much people rely on rail service in Great Britain, and how many disgruntled patrons there would be when delays occur. A recent study used real British Railway data and an artificial intelligence model to improve the ability to predict delays in railway networks. We wanted to explore this problem using our experience with graph neural networks, said Huy Tran, an aerospace engineering faculty member at the University of Illinois Urbana-Champaign. These are a specific class of artificial intelligence models that focus on data modeled as a graph, where a set of nodes are connected by edges.