A Recommendation System Supporting the Implementation of Sustainable Risk Management Measures in Airport Operations

Abstract

This paper introduces a recommendation system aimed at enhancing the sustainable process of risk management within airport operations, with a special focus on Occupational Stress Risks (OSRs). The recommendation system is implemented via a flexible Python code that offers seamless integration into various operational contexts. It leverages Fuzzy Cognitive Maps (FCMs) to conduct comprehensive risk assessments, subsequently generating prioritized recommendations for predefined risk management measures aimed at preventing and/or reducing the most critical OSRs. The system’s reliability has been validated by iterating the procedure with diverse input data (i.e., matrices of varying sizes) and measures. This confirms the system’s effectiveness across a broad spectrum of engineering scenarios.

Keywords

• recommendation system
• networks and applications
• uncertainty modeling