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Aiming at validly improving the efficiency and quality of hospital expert consultation, a consensus model under uncertainty is established to operate a hospital decision support system (HDSS). Considering that expert consultation is commonly used in emergency events associated with life rescue where uncertainty and complexity exist, hesitant fuzzy linguistic terms are adopted. Additionally, since pairwise comparison information is efficient to express individual judgment, a novel concept of satisfaction degree toward hesitant fuzzy linguistic preference relation is utilized to measure the group consensus. A trust-recommendation mechanism is built to generate advice for experts. A consensus model is constructed to handle the HDSS in emergency decision-making problems. Some simulation experiments are designed to verify the availability and reasonability of the proposed model. Then, the proposed model is applied to address the selection of an emergency response plan for the influenza H7N9 virus, and finally, the strong robustness and powerful capability of the proposed model in the consensus reaching process is exhibited by making a comparative analysis among several recommendation mechanisms.
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Stored only when both papers are in the corpus — 27 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.