Adopting effective hierarchal IoMTs computing with K-efficient clustering to control and forecast COVID-19 cases.
- DOI
- 10.1016/j.compeleceng.2022.108472
- Published
- 2022 Dec
- Container
- Computers & electrical engineering : an international journal
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1016/j.compeleceng.2022.108472,
title = {Adopting effective hierarchal IoMTs computing with K-efficient clustering to control and forecast COVID-19 cases.},
author = {Al-Khafaji HMR and Jaleel RA},
year = {2022},
journal = {Computers \& electrical engineering : an international journal},
doi = {10.1016/j.compeleceng.2022.108472},
url = {https://doi.org/10.1016/j.compeleceng.2022.108472}
}RIS
TY - JOUR TI - Adopting effective hierarchal IoMTs computing with K-efficient clustering to control and forecast COVID-19 cases. AU - Al-Khafaji HMR AU - Jaleel RA PY - 2022 JO - Computers & electrical engineering : an international journal DO - 10.1016/j.compeleceng.2022.108472 UR - https://doi.org/10.1016/j.compeleceng.2022.108472 ER -
APA
HMR, A., & RA, J. (2022). Adopting effective hierarchal IoMTs computing with K-efficient clustering to control and forecast COVID-19 cases.. Computers & electrical engineering : an international journal. https://doi.org/10.1016/j.compeleceng.2022.108472
Source records
- pubmed · retrieved 2026-09-26T17:56:24.887Z
- europe-pmc · retrieved 2026-09-26T17:56:24.899Z