A new prediction approach of the COVID-19 virus pandemic behavior with a hybrid ensemble modular nonlinear autoregressive neural network.

Melin P, Monica JC, Sanchez D, Castillo O

DOI: 10.1007/s00500-020-05452-z
Published: 2023
Container: Soft computing
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1007/s00500-020-05452-z,
  title = {A new prediction approach of the COVID-19 virus pandemic behavior with a hybrid ensemble modular nonlinear autoregressive neural network.},
  author = {Melin P and Monica JC and Sanchez D and Castillo O},
  year = {2023},
  journal = {Soft computing},
  doi = {10.1007/s00500-020-05452-z},
  url = {https://doi.org/10.1007/s00500-020-05452-z}
}

RIS

TY  - JOUR
TI  - A new prediction approach of the COVID-19 virus pandemic behavior with a hybrid ensemble modular nonlinear autoregressive neural network.
AU  - Melin P
AU  - Monica JC
AU  - Sanchez D
AU  - Castillo O
PY  - 2023
JO  - Soft computing
DO  - 10.1007/s00500-020-05452-z
UR  - https://doi.org/10.1007/s00500-020-05452-z
ER  -

APA

P, M., JC, M., D, S., & O, C. (2023). A new prediction approach of the COVID-19 virus pandemic behavior with a hybrid ensemble modular nonlinear autoregressive neural network.. Soft computing. https://doi.org/10.1007/s00500-020-05452-z

Source records

pubmed · retrieved 2026-09-26T02:29:40.780Z
europe-pmc · retrieved 2026-09-26T02:29:40.791Z