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

IF 1.8 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Algorithms Pub Date : 2023-11-07 DOI:10.3390/a16110511
Silvia Carpitella, Bruno Brentan, Antonella Certa, Joaquín Izquierdo
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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.
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支持在机场运作中推行可持续风险管理措施的建议系统
本文介绍了一个建议系统,旨在加强机场运营风险管理的可持续过程,特别关注职业压力风险(OSRs)。推荐系统是通过灵活的Python代码实现的,可以无缝集成到各种操作环境中。它利用模糊认知地图(fcm)进行全面的风险评估,随后为预先定义的风险管理措施生成优先建议,旨在预防和/或减少最严重的osr。通过对不同输入数据(即不同大小的矩阵)和测量方法进行迭代,验证了系统的可靠性。这证实了该系统在广泛的工程场景中的有效性。
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来源期刊
Algorithms
Algorithms Mathematics-Numerical Analysis
CiteScore
4.10
自引率
4.30%
发文量
394
审稿时长
11 weeks
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