Parallel prediction of dengue cases with different risks in Mexico using an artificial neural network model considering meteorological data
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00484-024-02643-3.pdf
Reference41 articles.
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2. Aburas HM, Cetiner BG, Sari M (2010) Dengue confirmed-cases prediction: a neural network model. Expert Syst Appl 37:4256–4260. https://doi.org/10.1016/j.eswa.2009.11.077
3. Ahmad S, Javeed S, Ahmad H et al (2021) Analysis and numerical solution of novel fractional model for dengue. Results Phys 28:104669. https://doi.org/10.1016/j.rinp.2021.104669
4. Báez-Hernández N, Casas-Martínez M, Danis-Lozano R, Velasco-Hernández JX (2017) A mathematical model for Dengue and Chikungunya in Mexico. BioRxiv:122556. https://doi.org/10.1101/122556
5. Campbell L, Luther C, Moo-Llanes D, Ramsey J, Danis-Lozano R, Peterson A (2015) Climate change influences on global distributions of dengue and chikungunya virus vectors. Philos Trans R Soc B Biol Sci 370(1665):1–9. https://doi.org/10.1098/rstb.2014.0135
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