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Association rules extraction for the identification of functional dependencies in complex technical infrastructures / Antonello, Federico (Milan, Polytech.) ; Baraldi, Piero (Milan, Polytech.) ; Shokry, Ahmed (Milan, Polytech. ; Ec. Polytech., Palaiseau (main)) ; Zio, Enrico (Milan, Polytech. ; Paris, Ecole des Mines ; Kyung Hee U.) ; Gentile, Ugo (CERN) ; Serio, Luigi (CERN)
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. [...]
2021 - Published in : Reliable Eng. Sys. Safety 209 (2021) 107305

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Identification of Critical Components in the Complex Technical Infrastructure of the Large Hadron Collider Using Relief Feature Ranking and Support Vector Machines / Shokry, Ahmed (Ec. Polytech., Palaiseau (main)) ; Baraldi, Piero (Milan, Polytech.) ; Castellano, Andrea (Milan, Polytech.) ; Serio, Luigi (CERN) ; Zio, Enrico (Milan, Polytech. ; U. PSL)
This work proposes a data-driven methodology for identifying critical components in Complex Technical Infrastructures (CTIs), for which the functional logic and/or the system structure functions are not known due the CTI’s complexity and evolving nature. The methodology uses large amounts of CTI monitoring data acquired over long periods of time and under different operating conditions. [...]
2021 - 19 p. - Published in : Energies 14 (2021) 6000

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A novel association rule mining method for the identification of rare functional dependencies in Complex Technical Infrastructures from alarm data / Antonello, Federico (Milan, Polytech.) ; Baraldi, Piero (Milan, Polytech.) ; Shokry, Ahmed (Milan, Polytech. ; Ec. Polytech., Palaiseau, CMLS) ; Zio, Enrico (Milan, Polytech. ; U. PSL ; Kyung Hee U.) ; Gentile, Ugo (CERN) ; Serio, Luigi (CERN)
This work presents a data-driven method for identifying rare functional dependencies among components of different systems of Complex Technical Infrastructures (CTIs) from large-scale databases of alarm messages. It is based on the representation of the alarm data in a binary form, the use of a novel association rule mining algorithm properly tailored for discovering rare dependencies among components of different systems and on the identification of groups of functionally dependent components. [...]
2021 - Published in : Expert Systems with Applications 170 (2021) 114560

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A Feature Selection-based Approach for the Identification of Critical Components in Complex Technical Infrastructures: Application to the CERN Large Hadron Collider / Baraldi, Piero (Milan, Polytech.) ; Castellano, Andrea (Milan, Polytech.) ; Shokry, Ahmed (Milan, Polytech.) ; Gentile, Ugo (CERN) ; Serio, Luigi (CERN) ; Zio, Enrico (Milan, Polytech. ; U. PSL ; Kyung Hee U.)
Complex Technical Infrastructures (CTIs) are large-scale systems made of tens of thousands of interdependent components organized in complex hierarchical architectures. They evolve in time in a way that at one point their functional logic may be more complex than originally designed, and, therefore, traditional reliability/risk importance measures cannot be used for identifying the critical components on which the protection and recovery efforts should be primarily allocated. [...]
2020 - Published in : Reliable Eng. Sys. Safety 201 (2020) 106974

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