668430-Roa

B.8. References 215 Madden, M. and P. Nolan (1999). “Monitoring and diagnosis of multiple incipient faults using fault tree induction”. In: IEE Proceedings: Control Theory and Applications 146.2, pp. 204–212. doi: 10.1049/IP-CTA:19990088. Madden, M. G. (1970). “Hierarchically structured inductive learning for fault diagnosis”. In: WIT Transactions on Information and Communication Technologies 20. doi: 10. 2495/AI980411. Madden, M. G. and P. J. Nolan (1994). “Generation of fault trees from simulated incipient fault case data”. In: WIT Transactions on Information and Communication Technologies 6. doi: 10.2495/AI940611. Mukherjee, S. and A. Chakraborty (2007). “Automated fault tree generation: bridging reliability with text mining”. In: 2007 Annual Reliability and Maintainability Symposium. IEEE, pp. 83–88. doi: 10.1109/RAMS.2007.328096. NASA (2002). Fault Tree Handbook with Aerospace Applications. Handbook. U.S. National Aeronautics and Space Administration. Nauta, M., D. Bucur, and M. Stoelinga (2018). “LIFT: Learning fault trees from observational data”. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 11024 LNCS, pp. 306–322. doi: 10.1007/978-3-319-99154-2_19. Quinlan, J. (1986). “Induction of Decision Trees”. In: Machine Learning 1.1, pp. 81–106. doi: 10.1023/A:1022643204877. Roth, M., M. Wolf, and U. Lindemann (2015). “Integrated Matrix-based Fault Tree Generation and Evaluation”. In: Procedia Computer Science 44. 2015 Conference on Systems Engineering Research, pp. 599–608. issn: 1877-0509. doi: 10.1016/j.procs. 2015.03.027. Waghen, K. and M.-S. Ouali (2019). “Interpretable logic tree analysis: A data-driven fault tree methodology for causality analysis”. In: Expert Systems with Applications 136, pp. 376–391. doi: 10.1016/j.eswa.2019.06.042. Waghen, K. and M.-S. Ouali (2021). “Multi-level interpretable logic tree analysis: A data-driven approach for hierarchical causality analysis”. In: Expert Systems with Applications 178, p. 115035. issn: 0957-4174. doi: 10.1016/j.eswa.2021.115035.

RkJQdWJsaXNoZXIy MjY0ODMw