Scholarlink

<p>Ship fire accidents represented a critical threat to maritime safety, yet the complex interrelationships among contributing factors remained insufficiently characterized due to methodological limitations in traditional analytical approaches. Conventional Decision-Making Trial and Evaluation Laboratory–Interpretive Structural Modeling (DEMATEL–ISM) methods relied on predetermined thresholds that might obscure the continuous nature of causal relationships and introduce subjective bias. Here a novel T-FR-AISM approach was developed that employs optimization algorithms to eliminate threshold dependency while preserving inherent uncertainty in expert assessments. By analyzing marine accident reports and publications from 2015 to 2023, 12 key influencing factors were identified across 6 dimensions: Person, Management, Equipment, Technology, Environment, and Psychology. Results revealed that Ship Management (B1), with the highest degree of centrality (<i>M</i> = 4.544), occupies the most fundamental position in the causal hierarchy. The optimized hierarchical structure identified a critical cross-dimensional intervention loop (A2-B2-C1) connecting management deficiencies to equipment failures and technical shortcomings. These findings provided actionable insights for maritime fire safety management, crew training program development, and regulatory framework enhancement.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A data-driven method for modeling factors in ship fire accidents by integrating Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Adversarial Interpretive Structural Modeling (AISM) based on Fuzzy Reachability Matrix (FR)

  • 期刊论文

  • 发表日期：

    2026年3月30日

查看全文
  • Kang Liu,
  • Cheng Fang,
  • Zihan Zhao

摘要

Ship fire accidents represented a critical threat to maritime safety, yet the complex interrelationships among contributing factors remained insufficiently characterized due to methodological limitations in traditional analytical approaches. Conventional Decision-Making Trial and Evaluation Laboratory–Interpretive Structural Modeling (DEMATEL–ISM) methods relied on predetermined thresholds that might obscure the continuous nature of causal relationships and introduce subjective bias. Here a novel T-FR-AISM approach was developed that employs optimization algorithms to eliminate threshold dependency while preserving inherent uncertainty in expert assessments. By analyzing marine accident reports and publications from 2015 to 2023, 12 key influencing factors were identified across 6 dimensions: Person, Management, Equipment, Technology, Environment, and Psychology. Results revealed that Ship Management (B1), with the highest degree of centrality (M = 4.544), occupies the most fundamental position in the causal hierarchy. The optimized hierarchical structure identified a critical cross-dimensional intervention loop (A2-B2-C1) connecting management deficiencies to equipment failures and technical shortcomings. These findings provided actionable insights for maritime fire safety management, crew training program development, and regulatory framework enhancement.