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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Singhal, Amit | |
| dc.date.accessioned | 2023-04-05T07:12:39Z | - |
| dc.date.available | 2023-04-05T07:12:39Z | - |
| dc.date.issued | 2020 | |
| dc.identifier.issn | 0960-0779 | |
| dc.identifier.uri | https://doi.org/10.1016/j.chaos.2020.110023 | |
| dc.identifier.uri | http://lrcdrs.bennett.edu.in:80/handle/123456789/1383 | - |
| dc.description.abstract | COVID-19, Discrete cosine transform (DCT), Fourier decomposition method (FDM), Gaussian mixture model (GMM), Mathematical model, Susceptible-infected-recovered (SIR) model | en_US |
| dc.publisher | Elsevier Ltd | en_US |
| dc.title | Modeling and prediction of COVID-19 pandemic using Gaussian mixture model | en_US |
| dc.type | Article | en_US |
| dc.indexed | sc | en_US |
| dc.indexed | WC | en_US |
| Appears in Collections: | Journal Articles_ECE | |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| 519.pdf Restricted Access | 2.21 MB | Adobe PDF | View/Open Request a copy |
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