Mining and Learning from Railway Safety Data with Graphs and Tensors
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2024-09-15
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Edition:June 1, 2023 – August 31, 2024
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Abstract:Railway systems are very complex pieces of cyberinfrastructure, interfacing with a number of transportation agents and other pieces of cyberinfrastructure. For instance, a railway crossing includes interactions between the railway system and a traffic intersection. Such a rich ecosystem of interactions among heterogeneous agents poses fascinating research challenges in modeling railway systems with data and conducting data-driven railway crossing safety assessment. In this project we leverage and extend powerful tensor and graph mining methods which can extract “needles in the haystack” within the abundance of collected data and produce actionable insights to better understand emerging accident patterns from historical data, identify underlying similarities in such patterns.
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