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基于混合区间型-2 模糊决策模型的高校 COVID-19 安全校园评估。

COVID-19 safe campus evaluation for universities by a hybrid interval type-2 fuzzy decision-making model.

机构信息

Faculty of Health Sciences, Department of Emergency Aid and Disaster Management, Munzur University, Tunceli, Turkey.

School of Transportation and Logistics, Istanbul University, 34320, Avcılar-Istanbul, Turkey.

出版信息

Environ Sci Pollut Res Int. 2023 Jan;30(3):8133-8153. doi: 10.1007/s11356-022-22796-1. Epub 2022 Sep 2.

Abstract

The fight against the COVID-19 pandemic, which has affected the whole world in recent years and has had devastating effects on all segments of society, has been one of the most important priorities. The Turkish Standards Institution has determined a checklist to contribute to developing safe and clean environments in higher education institutions in Turkey and to follow-up on infection control measures. However, this study is only a checklist that makes it necessary for decision-makers to make a subjective evaluation during the evaluation process, while the need to develop a more effective, systematic framework that takes into account the importance levels of multiple criteria has emerged. Therefore, this study applies the best-worst method under interval type-2 fuzzy set concept (IT2F-BWM) to determine the importance levels of criteria affecting the "COVID-19 safe campus" evaluation of universities in the context of global pandemic. A three-level hierarchy consisting of three main criteria, 11 sub-criteria, and 58 sub-criteria has been created for this aim. Considering the hierarchy, the most important sub-criterion was determined as periodic disinfection. The high contribution of the interval-valued type-2 fuzzy sets in expressing the uncertainty in the decision-makers' evaluations and the fact that BWM provides criterion weights with a mathematical optimization model that produces less pairwise comparisons and higher consistency are the main factors in choosing this approach. Simple additive weighting (SAW) has also been injected into the IT2F-BWM to determine the safety level of any university campus regarding COVID-19. Thus, decision-makers will be better prepared for the devastating effects of the pandemic by first improving the factors that are relatively important in the fight against the pandemic. In addition, a threshold value will be determined by considering all criteria, and it will prepare the ground for a road map for campuses. A case study is employed to apply the proposed model, and a comparison study is also presented with the Bayesian BWM to validate the results of the criteria weights.

摘要

近年来,全球范围内爆发的 COVID-19 疫情对社会各阶层造成了毁灭性影响,这场疫情的防控成为了重中之重。土耳其标准协会制定了一份清单,以促进土耳其高等教育机构安全、清洁环境的发展,并对感染控制措施进行跟踪。然而,这项研究只是一份清单,在评估过程中需要决策者进行主观评估,因此需要制定一个更有效、系统的框架,考虑到多个标准的重要程度。因此,本研究应用区间型 2 模糊集概念下的最佳最差方法(IT2F-BWM),以确定在全球大流行背景下影响大学“COVID-19 安全校园”评估的标准的重要程度。为此创建了一个由三个主要标准、11 个子标准和 58 个子标准组成的三级层次结构。考虑到层次结构,确定最关键的子标准为定期消毒。选择这种方法的主要因素是区间型 2 模糊集在表达决策者评估中的不确定性的高贡献,以及 BWM 提供了具有数学优化模型的标准权重,该模型产生的两两比较更少,一致性更高。还将简单加性加权(SAW)注入到 IT2F-BWM 中,以确定任何大学校园对 COVID-19 的安全程度。因此,决策者将通过首先改进在抗击大流行方面相对重要的因素,为大流行的破坏性影响做好更好的准备。此外,将通过考虑所有标准确定一个阈值,并为校园制定路线图奠定基础。通过案例研究应用提出的模型,并与贝叶斯 BWM 进行比较研究,验证标准权重的结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ce5/9438885/6feb5e429e24/11356_2022_22796_Fig1_HTML.jpg

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