{"id":131778,"date":"2020-12-11T17:15:59","date_gmt":"2020-12-11T14:15:59","guid":{"rendered":"https:\/\/en.buradabiliyorum.com\/predicting-british-railway-delays-using-artificial-intelligence\/"},"modified":"2020-12-11T17:15:59","modified_gmt":"2020-12-11T14:15:59","slug":"predicting-british-railway-delays-using-artificial-intelligence","status":"publish","type":"post","link":"https:\/\/buradabiliyorum.com\/en\/predicting-british-railway-delays-using-artificial-intelligence\/","title":{"rendered":"#Predicting British railway delays using artificial intelligence"},"content":{"rendered":"

“#Predicting British railway delays using artificial intelligence<\/strong>”<\/p>\n

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\n A train schedule at a station near London. Credit: Debra Levey Larson, University of Illinois Urbana-Champaign
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Over the past 20 years, the number of passengers travel<\/a>ing 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 from the University of Illinois Urbana-Champaign used real British Railway data and an artificial intelligence model to improve the ability to predict delays in railway networks.<\/p>\n

“We wanted to explore this problem using our experience with graph neural networks,” said Huy Tran, an aerospace engineering faculty member at UIUC. “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.”<\/p>\n

“This was a collaboration with Simon Hu, an expert on railway networks, from the Zhejiang University-University of Illinois Urbana-Champaign Institute,” Tran said. “We worked together to develop a new way to represent a rail network and app<\/a>ly it to real-world data to predict delays.”<\/p>\n

They applied the Spatial-Temporal Graph Convolutional Network model to predict delays within a portion of the British rail network where Didcot Parkway and Long Paddington serve as gateway stations.<\/p>\n

“Compared with other statistical models, this one outperforms them for forecasting delays up to 60 minutes in the future,” Tran said.<\/p>\n

He added that others have developed similar models for social<\/a> networks, but he wanted to apply it to an engineering problem.<\/p>\n


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