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Updated: Jun 21, 2025
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A novel sequential risk assessment model for analyzing commercial aviation accidents: Soft computing perspective
Amirhossein Nosrati Malekjahan1, Ali Husseinzadeh Kashan1, Seyed Mojtaba Sajadi2
1Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran.
Summary
This study introduces a structured model for analyzing commercial aviation accidents. It prioritizes risks using novel fuzzy techniques and fuzzy cognitive maps to enhance aviation safety.
Area of Science:
- Aviation Safety and Risk Management
- Decision Analysis
- Fuzzy Set Theory
Background:
- Commercial aviation faces numerous accidents, necessitating structured analysis.
- Existing risk assessment methods require enhancement for complex systems.
Purpose of the Study:
- To develop a comprehensive model for analyzing commercial aviation accidents.
- To introduce novel risk prioritization techniques for enhanced safety.
Main Methods:
- Failure Mode and Effects Analysis (FMEA) for risk identification.
- Multi-Attribute Decision Making (MADM) and novel fuzzy techniques (intuitionistic fuzzy sets, vague sets) for risk prioritization.
- Fuzzy Cognitive Maps (FCM) for analyzing risk factor interactions.
Main Results:
- The model effectively identifies and prioritizes critical risks in commercial aviation.
- Novel fuzzy-based methods demonstrate robust handling of uncertainty in risk assessment.
- FCM analysis reveals key interactions among risk factors, aiding systemic understanding.
Conclusions:
- The proposed model offers a structured and effective approach to aviation accident analysis.
- The novel risk prioritization techniques provide valuable tools for managing aviation safety.
- The methodology is applicable to other complex transportation systems requiring risk assessment.
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