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A case-driven fuzzy reasoning framework for emergency decision-making under interval probabilistic linguistic information | ||
| Iranian Journal of Fuzzy Systems | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 04 آبان 1405 اصل مقاله (9.36 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22111/ijfs.2026.55280.9805 | ||
| نویسندگان | ||
| J. Zheng* 1، 2؛ Y. M. Wang3؛ K. Zhang4؛ J. Q. Gao5 | ||
| 1Department of Electronics Information Science, Fujian Jiangxia University, Fujian 350108, PR China. | ||
| 2Research Institute for Data Analysis and Intelligent Decision Making in Fujian Jiangxia University, Fujian Jiangxia University, Fuzhou Fujian 350108, PR China. | ||
| 3Institute of Decision Science, Fuzhou University, Fuzhou 350108, Fujian, China | ||
| 4Department of Information Engineering, Fujian Chuanzheng Communications College, Fuzhou 350007, Fujian, China | ||
| 5College of Electronics and Information Science, Fujian Jiangxia University, Fuzhou 350108, Fujian, China | ||
| چکیده | ||
| Case-driven fuzzy reasoning (CDFR) enhances emergency response efficiency by leveraging historical experience and evaluation information. However, existing CDFR models lack a systematic framework for multi-source information fusion and fail to adequately address the fuzziness regarding information reliability and inter-group consensus. To bridge this gap, this paper proposes a CDFR framework for emergency decision-making under interval probabilistic linguistic information. The reasoning process commences with fuzzy case retrieval to establish the decision context. Multi-source information is then pre-processed through reliability measure and consensus-driven adjustment mechanism to ensure the credibility and consistency of the evaluation information. Furthermore, attribute weights are derived via the IPLTS- embedded DEMATEL method, and group-wise evaluation information is then fused using the IPLTSWG operator. Finally, an interval-based GLDS approach is proposed to generate the final ranking, which preserves the uncertainty of the original information throughout the reasoning chain. The practicability of the proposed framework is demonstrated through a case study of public health emergency response. | ||
| کلیدواژهها | ||
| Case-driven fuzzy reasoning؛ multi-group collaboration؛ emergency response؛ interval probabilistic linguistic term sets؛ DEMATEL؛ GLDS | ||
| مراجع | ||
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