A Multi-Objective Evolutionary Algorithm (MOEA) is proposed for the identification of association rules describing functional dependencies in Complex Technical Infrastructures (CTIs). The algorithm uses novelty search to explore the solution space. It has been applied to a real large-scale database of alarms collected in the CTI of CERN (European Organization for Nuclear Research). The obtained results show its effectiveness in identifying rare functional dependencies not found using standard algorithms of Association Rule Mining (ARM) algorithms.

Multi-objective evolutionary algorithm for the identification of rare functional dependencies in complex technical infrastructures

Antonello F.;Baraldi P.;Zio E.;
2020

Abstract

A Multi-Objective Evolutionary Algorithm (MOEA) is proposed for the identification of association rules describing functional dependencies in Complex Technical Infrastructures (CTIs). The algorithm uses novelty search to explore the solution space. It has been applied to a real large-scale database of alarms collected in the CTI of CERN (European Organization for Nuclear Research). The obtained results show its effectiveness in identifying rare functional dependencies not found using standard algorithms of Association Rule Mining (ARM) algorithms.
30th European Safety and Reliability Conference, ESREL 2020 and 15th Probabilistic Safety Assessment and Management Conference, PSAM 2020
Complex technical infrastructures, dependent abnormal behaviours, alarms, rare association rules, multi objective evolutionary algorithm
Genetic algorithm
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1181267
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