Coverage-Based Variable Precision (I, PSO)-Fuzzy Rough Sets with Applications to Emergency Decision-Making
Abstract Considering the characteristics of imprecise, incomplete and fuzzy data in emergency environment, a novel emergency decision-making method based on coverage-based variable precision (I, PSO)-fuzzy rough set model is proposed. First, an improved (I, PSO)-fuzzy rough set model is proposed, wh...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-02-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44196-024-00728-w |
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| Summary: | Abstract Considering the characteristics of imprecise, incomplete and fuzzy data in emergency environment, a novel emergency decision-making method based on coverage-based variable precision (I, PSO)-fuzzy rough set model is proposed. First, an improved (I, PSO)-fuzzy rough set model is proposed, which combines the covering-based fuzzy rough set (CFRS) and the variable precision fuzzy rough set (VPFRS). Second, inspired by the idea of attribute reduction, a novel method for determining attribute weights is introduced to optimize weight assignment in emergency decision-making. Last but not least, to illustrate the feasibility and effectiveness of the proposed method, an example of post-flood rescue force allocation in urban areas is demonstrated. Finally, the stability and superiority of the method are verified through sensitivity analysis and comparative evaluation. |
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| ISSN: | 1875-6883 |