Published October 15, 2021
| Version 1.1
Conference paper
Open
Data-driven inference of fault tree models exploiting symmetry and modularization
Authors/Creators
- 1. University of Twente
Description
This dataset contains (i) the Python source code of the SymLearn toolchain and the improved implementation of the FT-MOEA algorithm (used to infer Fault Tree models in a data-driven manner); (ii) the failure dataset for five case studies. The latter used as input to our implementation; and (iii) the results obtained from our toolchain for the case studies.
Notes
This research has been partially funded by Dutch Research Council (NWO) under the grant PrimaVera (https://primavera-project.com) number NWA.1160.18.238.
Files
p3_SymLearn.zip
Files
(59.9 MB)
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