Zhou, Zixuan (2023) Predictive Analysis for COVID-19 Cases in India Based on LSTM Algorithms. In: Proceedings of the International Conference on Financial Innovation, FinTech and Information Technology, FFIT 2022, October 28-30, 2022, Shenzhen, China.
![[thumbnail of 53625.pdf]](http://eprints.eai.eu/style/images/fileicons/application_pdf.png "53625.pdf")
PDF
53625.pdf
Download (315kB)
Abstract
COVID-19 continues to hurt the global economy and living standards. As the number of confirmed cases rises, it is crucial to predict COVID-19 transmission and treatment effectively. This paper aims to compare the results under different machine learning methods and improve the efficiency of predicti
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Date Deposited: | 04 Mar 2026 16:10 |
| Last Modified: | 17 Apr 2026 03:23 |
| URI: | http://eprints.eai.eu/id/eprint/42639 |
Actions (login required)
- View Item