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Association rules extraction for the identification of functional dependencies in complex technical infrastructures
This work proposes a method for identifying functional dependencies among components of complex technical infrastructures using databases of alarm messages. The developed method is based on the representation of the alarm database by a binary matrix, the use of the Apriori algorithm for mining assoc...
| Autores principales: | , , , , , |
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| Lenguaje: | eng |
| Publicado: |
2021
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1016/j.ress.2020.107305 http://cds.cern.ch/record/2809708 |
| _version_ | 1780973173848670208 |
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| author | Antonello, Federico Baraldi, Piero Shokry, Ahmed Zio, Enrico Gentile, Ugo Serio, Luigi |
| author_facet | Antonello, Federico Baraldi, Piero Shokry, Ahmed Zio, Enrico Gentile, Ugo Serio, Luigi |
| author_sort | Antonello, Federico |
| collection | CERN |
| description | This work proposes a method for identifying functional dependencies among components of complex technical infrastructures using databases of alarm messages. The developed method is based on the representation of the alarm database by a binary matrix, the use of the Apriori algorithm for mining association rules and a new algorithm for identifying groups of functionally dependent components. The effectiveness of the proposed method is shown by means of its application to an artificial case study and a real large-scale database of alarms generated by different supervision systems of the complex technical infrastructure of CERN (European Organization for Nuclear Research). |
| id | cern-2809708 |
| institution | Organización Europea para la Investigación Nuclear |
| language | eng |
| publishDate | 2021 |
| record_format | invenio |
| spelling | cern-28097082022-05-19T18:54:39Zdoi:10.1016/j.ress.2020.107305http://cds.cern.ch/record/2809708engAntonello, FedericoBaraldi, PieroShokry, AhmedZio, EnricoGentile, UgoSerio, LuigiAssociation rules extraction for the identification of functional dependencies in complex technical infrastructuresData Analysis and StatisticsComputing and ComputersThis work proposes a method for identifying functional dependencies among components of complex technical infrastructures using databases of alarm messages. The developed method is based on the representation of the alarm database by a binary matrix, the use of the Apriori algorithm for mining association rules and a new algorithm for identifying groups of functionally dependent components. The effectiveness of the proposed method is shown by means of its application to an artificial case study and a real large-scale database of alarms generated by different supervision systems of the complex technical infrastructure of CERN (European Organization for Nuclear Research).oai:cds.cern.ch:28097082021 |
| spellingShingle | Data Analysis and Statistics Computing and Computers Antonello, Federico Baraldi, Piero Shokry, Ahmed Zio, Enrico Gentile, Ugo Serio, Luigi Association rules extraction for the identification of functional dependencies in complex technical infrastructures |
| title | Association rules extraction for the identification of functional dependencies in complex technical infrastructures |
| title_full | Association rules extraction for the identification of functional dependencies in complex technical infrastructures |
| title_fullStr | Association rules extraction for the identification of functional dependencies in complex technical infrastructures |
| title_full_unstemmed | Association rules extraction for the identification of functional dependencies in complex technical infrastructures |
| title_short | Association rules extraction for the identification of functional dependencies in complex technical infrastructures |
| title_sort | association rules extraction for the identification of functional dependencies in complex technical infrastructures |
| topic | Data Analysis and Statistics Computing and Computers |
| url | https://dx.doi.org/10.1016/j.ress.2020.107305 http://cds.cern.ch/record/2809708 |
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