Evidence map›Paper›PMID 38977405›Full record

ArticleRisk analysis : an official publication of the Society for Risk Analysis2025

A novel sequential risk assessment model for analyzing commercial aviation accidents: Soft computing perspective.

Amirhossein Nosrati Malekjahan, Ali Husseinzadeh Kashan, Seyed Mojtaba Sajadi

Abstract read
In one paragraph

Article in Risk analysis : an official publication of the Society for Risk Analysis, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. A novel sequential risk assessment model for analyzing commercial aviation accidents: Soft computing perspective.Risk analysis : an official publication of the Society for Risk Analysis · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Amirhossein Nosrati MalekjahanFaculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran.ORCID https://orcid.org/0000-0002-4955-2813
Ali Husseinzadeh KashanFaculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran.
Seyed Mojtaba SajadiOperations and Information Management Department, Aston Business School, Aston University Birmingham, Birminghamm, UK.ORCID https://orcid.org/0000-0002-2139-2053

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to the importance of the commercial aviation system and, also, the existence of countless accidents and unfortunate occurrences in this industry, there has been a need for a structured approach to deal with them in recent years. Therefore, this study presents a comprehensive and sequential model for analyzing commercial aviation accidents based on historical data and reports. The model first uses the failure mode and effects analysis (FMEA) technique to determine and score existing risks; then, the risks are prioritized using two multi-attribute decision making (MADM) methods and two novel and innovative techniques, including ranking based on intuitionistic fuzzy risk priority number and ranking based on the vague sets. These techniques are based in an intuitionistic fuzzy environment to handle uncertainties and the FMEA features. A fuzzy cognitive map is utilized to evaluate existing interactions among the risk factors, and additionally, various scenarios are implemented to analyze the role of each risk, group of risks, and behavior of the system in different conditions. Finally, the model is performed for a real case study to clarify its applicability and the two novel risk prioritization techniques. Although this model can be used for other similar complex transportation systems with adequate data, it is mainly employed to illustrate the most critical risks and for analyzing existing relationships among the concepts of the system.

Indexed as

aviation accidentsFMEAfuzzy cognitive mapintuitionistic fuzzy environmentrisk assessment

Identifiers

PMID38977405
PMCPMC11735343

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.