ArticleExpert systems with applications2023
COVID-19 medical waste transportation risk evaluation integrating type-2 fuzzy total interpretive structural modeling and Bayesian network.
Article in Expert systems with applications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Experimental study on recycling rubber to increase the impact resistance of cement mortar.Scientific reports · 2024Article
- A comprehensive protocol for evaluating health, safety, and environmental risks of hospital solid waste through FMEA technique.MethodsX · 2024Article
- An application of BWM for risk control in reverse logistics of medical waste.Frontiers in public health · 2024Article
- Risk Management for Whole-Process Safe Disposal of Medical Waste: Progress and Challenges.Risk management and healthcare policy · 2024Review
- Interval type-2 Fuzzy control and stochastic modeling of COVID-19 spread based on vaccination and social distancing rates.Computer methods and programs in biomedicine · 2023Article
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Authors and funding
3 authors.
Funding
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Abstract
With the amount of medical waste rapidly increasing since the corona virus disease 2019 (COVID-19) pandemic, medical waste treatment risk evaluation has become an important task. The transportation of medical waste is an essential process of medical waste treatment. This paper aims to develop an integrated model to evaluate COVID-19 medical waste transportation risk by integrating an extended type-2 fuzzy total interpretive structural model (TISM) with a Bayesian network (BN). First, an interval type-2 fuzzy based transportation risk rating scale is introduced to help experts express uncertain evaluation information, in which a new double alpha-cut method is developed for the defuzzification of the interval type-2 fuzzy numbers (IT2FNs). Second, TISM is combined with IT2FNs to construct a hierarchical structural model of COVID-19 medical waste transportation risk factors under a high uncertain environment; a new bidirectional extraction method is proposed to describe the hierarchy of risk factors more reasonably and accurately. Third, the BN is integrated with IT2FNs to make a comprehensive medical waste transportation risk evaluation, including identifying the sensitive factors and diagnosing the event's causation. Then, a case study of COVID-19 medical waste transportation is displayed to demonstrate the effectiveness of the proposed model. Further, a comparison of the proposed model with the traditional TISM and BN model is conducted to stress the advantages of the proposed model.
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Registered trials
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