Project objectives
The project aims to develop a risk assessment methodology that combines machine learning techniques with the expertise of human experts. Specifically, machine learning techniques are quite effective when sufficient data is available, but they are inflexible and do not provide insight into why inputs are mapped into outputs. In contrast, decision support systems based on human expert knowledge are able to account for intangible factors and decision-makers' intuition, but typically involve ambiguous or contradictory information. The project aims to combine these two domains to achieve a multifaceted and expressive risk analysis framework, which will be applied to scenarios such as biofuel production and Seveso plants in general.
Official Website: www.emergentrisk.it
Start and end date
2020 - 2024
Project Manager
Prof. Roberto Setola - Full Professor of Automatics - Director of the Complex Systems and Security Laboratory
Coordinating institution of the project
Università Campus Bio-Medico di Roma
Other Institutions involved
University of Messina; University of Genoa; INAIL
Funding source(s).
INAIL
