Caricamento...
Time series prediction for the epidemic trends of COVID-19 using the improved LSTM deep learning method: Case studies in Russia, Peru and Iran
The COVID-19 outbreak in late December 2019 is still spreading rapidly in many countries and regions around the world. It is thus urgent to predict the development and spread of the epidemic. In this paper, we have developed a forecasting model of COVID-19 by using a deep learning method with rollin...
Salvato in:
| Pubblicato in: | Chaos Solitons Fractals |
|---|---|
| Autori principali: | , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Elsevier Ltd.
2020
|
| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7437443/ https://ncbi.nlm.nih.gov/pubmed/32839643 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.chaos.2020.110214 |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne! !
|