dc.contributor.author |
Caldera, Nuwan |
|
dc.date.accessioned |
2023-01-17T04:51:21Z |
|
dc.date.available |
2023-01-17T04:51:21Z |
|
dc.date.issued |
2022 |
|
dc.identifier.citation |
Caldera, Nuwan (2022) Corona ( Covid - 19 ) patient prediction approach. MSc. Dissertation, Informatics Institute of Technology |
en_US |
dc.identifier.issn |
20191280 |
|
dc.identifier.uri |
http://dlib.iit.ac.lk/xmlui/handle/123456789/1431 |
|
dc.description.abstract |
The Covid 19 virus is a deadly virus that has currently spread around the world. This report entails a solution to prevent this virus. It includes an introduction with the problem domain, project aims and objectives in addition to a literature survey with a comprehensive analysis on all the existing solutions and caparisons among them. The System requirement specification, SLEP, and project methodology comprise of the first five chapters in this report. The way the prototype is implemented with evidence of the codebase will be included in the implementation chapter. Furthermore, the report includes all testing types such as black box and white box testing while the methodology for evaluating the prototype is analyzed in-depth. The proposed solution will essentially contribute to save numerous human lives affected from COVID-19 in the future. |
en_US |
dc.language.iso |
en |
en_US |
dc.subject |
Covid |
en_US |
dc.subject |
Corona |
en_US |
dc.subject |
Prediction |
en_US |
dc.subject |
Analytics |
en_US |
dc.title |
Corona ( Covid - 19 ) patient prediction approach |
en_US |
dc.type |
Thesis |
en_US |