Mrkov Chains with COVID_19 Application
| dc.contributor.advisor | Mark Holland | |
| dc.contributor.author | nora khalaf mohammed Aldosari | |
| dc.date | 2020 | |
| dc.date.accessioned | 2022-05-29T10:56:43Z | |
| dc.date.available | 2022-05-29T10:56:43Z | |
| dc.degree.department | Mathematics | |
| dc.degree.grantor | College of Engineering ,mathematics and physical science s | |
| dc.description.abstract | The main subject of this work is studying the dynamics of the number of infected, dead and recovered COVID_19 cases in Saudi Arabia over the past 6 months using discrete continuous- time Markov chain. The data model was chosen due to the fact that the dynamics of these processes are different from the main classical deterministic processes, such as the SIR model. | |
| dc.identifier.uri | https://drepo.sdl.edu.sa/handle/20.500.14154/45923 | |
| dc.language.iso | en | |
| dc.title | Mrkov Chains with COVID_19 Application | |
| sdl.thesis.level | Master | |
| sdl.thesis.source | SACM - United Kingdom |