Analysis of the relationships among global stock markets is crucial for international investors, regulators, and policymakers, particularly during a crisis. Complex network theory was applied to analyze the relationship between global stock markets during the Russia-Ukraine war. Daily data from...

This study presents a prescriptive analytics framework for optimal intelligent predictive maintenance of railway tracks. We use machine learning and Graph Convolutional Networks (GCNs) to optimize the maintenance schedules for railway infrastructure and enhance operational efficiency and safety....

This study examines the evolution of public debt among the 27 EU member states using Graph Theory tools; the Threshold Weighted-Minimum Dominating Set (TW-MDS) and the k-core decomposition method, alongside a standard network quantitative metric, the density. By separating the data into three...