Real-time forecasting of the COVID 19 using fuzzy grey Markov: a different approach in decision-making
Author:
Funder
Akademi Sains Malaysia
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Computational Mathematics
Link
https://link.springer.com/content/pdf/10.1007/s40314-022-01949-5.pdf
Reference39 articles.
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2. Baz A, Alhakami A, Alshareef E (2020) A framework of computational model for predicting the spread of COVID-19 pandemic in Saudi Arabia. Int J Intell Eng Syst 13(5):463–475. https://doi.org/10.22266/ijies2020.1031.41
3. Bherwani H (2020) Understanding Covid-19 transmission through Bayesian probabilistic modeling and GIS-based Voronoi approach: a policy perspective. Environ Dev Sustain 23:5846–5864. https://doi.org/10.1007/s10668-020-00849-0
4. Boccaletti S, Ditto W, Mindlin G, Atangana A (2020) Modeling and forecasting of epidemic spreading: the case of Covid-19 and beyond. Chaos Solitons Fractals 135:109794. https://doi.org/10.1016/j.chaos.2020.109794
5. Castillo O, Melin P (2020) Forecasting of Covid-19 time series for countries in the world based on a hybrid approach combining the fractal dimension and fuzzy logic. Chaos Solitons Fractals 140:110242. https://doi.org/10.1016/j.chaos.2020.110242
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. An intuitionistic fuzzy grey-Markov method with application to demand forecasting for emergency supplies during major epidemics;Grey Systems: Theory and Application;2023-11-06
2. HMC-COVID-19: Hidden Markov Chains Model for COVID-19 Diagnosis;2023 International Conference on Decision Aid Sciences and Applications (DASA);2023-09-16
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