by Vaibhavi Tiwari, Ola Suaifan, Ramy Othman and Anand Gupta
Journal of Engineering Research and Sciences, Volume 5, Issue 6, Page # 67-96, 2026; DOI: 10.55708/js0506006
Abstract: Graph Neural Networks (GNNs) have emerged as a promising approach for fault diagnosis in complex cyber-physical systems because they can model intercomponent relationships, fault propagation, and system-level anomalies across domains such as industrial automation, smart grids, transportation, and healthcare. This survey presents a multidimensional review of GNN-based fault diagnostics, organizing existing methods according to graph… Read More

(This article belongs to the Section Interdisciplinary Applications – Computer Science (IAC))