加权
互联网
后悔
随机优势
计算机科学
排名(信息检索)
优势(遗传学)
人工智能
运筹学
统计
机器学习
医学
数学
万维网
基因
生物化学
放射科
化学
作者
Fan Liu,Huchang Liao,Xin Wu,Abdullah Al-Barakati
标识
DOI:10.1016/j.ins.2023.02.061
摘要
Internet hospitals are platforms that provide medical information, prescription, and treatment by combining online and offline medical resources. Well-development Internet hospitals can reduce operational pressure of offline hospitals and unnecessary waste of medical resources. Evaluating the performance of Internet hospitals is helpful for their development. In this paper, we introduce a linguistic Z-number-based gained and lost dominance score (GLDS) method to evaluate Internet hospitals. Firstly, to ensure the reliability of evaluation information, we extend the GLDS method to the linguistic Z-number environment. To model the risk preference of an expert, we depict the negative performance of an alternative over other alternatives under each criterion by a lost dominance score function, and represent the individual regret of a expert to the worst alternative by a net lost dominance score function. A weighting method that combines the best worst method and correlation coefficient method is developed to determine the weights of criteria. To verify the validity and practicability of the proposed method, a case study of ranking Internet hospitals is provided. Comparative analysis shows that the solutions of the proposed method reflect the preferences of experts.
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