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Identifying key factors in building fires: A novel approach fusing K-shell entropy gravity
Yongping Yu1, Ning Wang1, Shibo Cui1
1School of Economics and Management, Dalian University of Technology, Liaoning, China.
Plos One
|June 5, 2026
Summary
A new K-shell Entropy Gravity (KEG) algorithm accurately identifies key building fire factors by analyzing complex network relationships. This method enhances fire prevention strategies by pinpointing critical elements influencing fire initiation and spread.
Area of Science:
- Fire Science and Engineering
- Network Science
- Risk Analysis
Background:
- Accurate identification of key factors is essential for effective building fire prevention strategies.
- Existing methods may not fully capture the complex interdependencies and propagation dynamics of fire incidents.
Purpose of the Study:
- To propose a novel K-shell Entropy Gravity (KEG) algorithm for improved accuracy in identifying critical building fire factors.
- To develop a robust analytical tool for understanding and mitigating building fire risks.
Main Methods:
- Constructed a complex network representing relationships between fire influencing factors.
- Developed a composite attribute integrating K-shell value, information entropy difference, and shortest path length to quantify node importance.
- Applied a gravity-based model incorporating these metrics to assess node influence and identify key factors.
- Validated the KEG algorithm against baseline methods (SIR model) and evaluated using building fire datasets from California and Alaska.
Main Results:
- The KEG algorithm demonstrated superior accuracy in identifying critical building fire factors compared to baseline methods.
- Sensitivity analysis confirmed the significant impact of identified key factors on accident propagation.
- Ablation experiments and cross-dataset validation (California, Alaska) confirmed the method's robustness.
Conclusions:
- The proposed KEG algorithm provides a reliable and accurate analytical tool for identifying key factors in building fires.
- Findings support the development of more targeted and effective fire prevention and mitigation strategies.
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