对数
等级制度
计算机科学
控制论
2019年冠状病毒病(COVID-19)
模糊逻辑
人工智能
度量(数据仓库)
中医药
价值(数学)
数据挖掘
数学
机器学习
医学
疾病
传染病(医学专业)
替代医学
市场经济
数学分析
病理
经济
作者
Yuhe Fu,Chonghui Zhang,Yujuan Chen,Fengshou Gu,Tomas Baležentis,Dalia Štreimikienė
出处
期刊:Kybernetes
[Emerald (MCB UP)]
日期:2021-06-29
卷期号:51 (8): 2461-2480
被引量:1
标识
DOI:10.1108/k-11-2020-0822
摘要
Purpose The proposed DHHFLOWLAD is used to design a recommendation system, which aims to provide the most appropriate treatment to the patient under a double hierarchy hesitant fuzzy linguistic environment. Design/methodology/approach Based on the ordered weighted distance measure and logarithmic aggregation, we first propose a double hierarchy hesitant fuzzy linguistic ordered weighted logarithmic averaging distance (DHHFLOWLAD) measure in this paper. Findings A case study is presented to illustrate the practicability and efficiency of the proposed approach. The results show that the recommendation system can prioritize TCM treatment plans effectively. Moreover, it can cope with pattern recognition problems efficiently under uncertain information environments. Originality/value An expert system is proposed to combat COVID-19 that is an emerging infectious disease causing disruptions globally. Traditional Chinese medicine (TCM) has been proved to relieve symptoms, improve the cure rate, and reduce the death rate in clinical cases of COVID-19.
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