Ranking COVID-19 vaccines using fuzzy TOPSIS method

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bracu.type.groupResearch Publications
datacite.rightsMetadata Only
dc.contributor.authorPaul, Suprova
dc.contributor.authorPervez, Tamanna
dc.contributor.authorRabiul Alam, Md. Golam
dc.contributor.departmentDepartment of Computer Science and Engineering
dc.date.accessioned2026-08-27T03:47:28Z
dc.date.available2026-08-27T03:47:28Z
dc.date.issued2023-01-01
dc.description.abstractSince the outbreak of COVID-19, researchers around the world are trying to develop and vaccinate world communities. Selecting the suitable and cost-effective vaccine for a country is a Multi-Criteria Decision-Making (MCDM) problem involving several conflicting criteria on which the decision maker's knowledge is not precise. This work develops a Fuzzy TOPSIS approach in order to find a suitable COVID-19 vaccine. We used a total of eight well-known available vaccines and considered six main criteria based on various complexity, efficiency, and cost considerations. We evaluated the weights of numerous criteria and the ratings of each alternative vaccine by parameterizing a set of pre-defined linguistic variables using triangular fuzzy numbers. Final rankings of COVID-19 vaccines are obtained using the Fuzzy TOPSIS approach.
dc.description.versionPublished
dc.format.extent6 Pages
dc.identifier.citationM. M. R. N. Gazi, R. F. Nisa, N. S. Oishe, M. M. Fiona, S. M. A. Maruf and S. K. Ghosh, "Hybrid Deep Learning Framework for Rainfall Prediction: Integrating Wavelet-ARIMA, CEEMDANLSTM, and CNN-BiLSTM for Enhanced Climate Variability Analysis," 2025 International Conference on NexGen Networks and Cybernetics (IC2NC), Erode, India, 2025, pp. 781-788, doi: 10.1109/IC2NC67409.2025.11376471.
dc.identifier.doi10.1109/IC3S57698.2023.10169848
dc.identifier.issn9798350325904
dc.identifier.other2-s2.0-85166219735
dc.identifier.urihttps://hdl.handle.net/10361/29539
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.hasversion10.1109/IC3S57698.2023.10169848
dc.relation.ispartof2023 International Conference on Communication Circuits and Systems Ic3s 2023
dc.relation.ispartofseries2023 International Conference on Communication Circuits and Systems Ic3s 2023
dc.relation.urihttps://ieeexplore.ieee.org/document/10169848
dc.subjectDeep learning
dc.subjectAdaptation models
dc.subjectClimate variability
dc.subjectPredictive models
dc.subjectWavelet analysis
dc.subjectData models
dc.subjectWater resources
dc.subjectKeywords- rainfall prediction
dc.subjectHybrid deep learning
dc.subjectCEEMDAN-LSTM
dc.subjectWavelet decomposition
dc.subjectCNN-BiLSTM
dc.subjectClimate variability analysis
dc.subject.lcshCOVID-19 (Disease)--Vaccination.
dc.subject.lcshFuzzy logic.
dc.titleRanking COVID-19 vaccines using fuzzy TOPSIS method
dc.typeConference Proceeding
person.affiliation.nameBRAC University
person.affiliation.nameChittagong University of Engineering and Technology
person.affiliation.nameBRAC University
person.identifier.scopus-author-id58513419900
person.identifier.scopus-author-id58512687400
person.identifier.scopus-author-id57289396600

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