Synthesis of Non-Conventional Predictive Models based on Multivariate Analysis
Deadline: 27/01/2026
Scientific-Disciplinary Group
09 - Industrial And Information Engineering
Description
The overall project aims to explore systematic machine-learning techniques for fault detection and predictive maintenance in industrial production. More specifically, it focuses on using non-conventional approaches that merge multivariate analysis with information-theoretic methods. The intended applications mainly concern two areas, although they are not limited to them. The first area concerns the reliability of power-conversion systems, in line with the objectives of the ECS4DRES research project. The second area concerns reliability issues related to aerospace engineering.
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Funding body
ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - CENTRO RICERCA SISTEMI ELETTRONICI INGEGN.INF. E TELECOM."ERCOLE DE CASTRO"
How to apply
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View the original posting on the MUR website: Go to MUR website