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Exact Forecasting for COVID-19 Data: Case Study for Turkey

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dc.contributor.author Dinçkal, Çiğdem
dc.date.accessioned 2024-03-20T13:00:27Z
dc.date.available 2024-03-20T13:00:27Z
dc.date.issued 2021
dc.identifier.citation Dinçkal, Ç. (2021). "Exact Forecasting for COVID-19 Data: Case Study for Turkey", Advances in Data Science and Adaptive Analysis, Vol.13, No.2. tr_TR
dc.identifier.issn 2424-9238
dc.identifier.uri http://hdl.handle.net/20.500.12416/7652
dc.description.abstract The novel coronavirus COVID-19 (SARS-CoV-2) with the first clinical case emerged in the city of Wuhan in China in December 2019. Then it has spread to the entire world in very short time and turned into a global problem, namely, it has rapidly become a pandemic. Within this context, many studies have attempted to predict the consequences of the pandemic in certain countries. Nevertheless, these studies have focused on some parameters such as reproductive number, recovery rate and mortality rate when performing forecasting. This study aims to forecast COVID-19 data in Turkey with use of a new technique which is a combination of classical exponential smoothing and moving average. There is no need for reproductive number, recovery rate and mortality rate computation in this proposed technique. Simulations are carried out for the number of daily cases, active cases (those are cases with no symptoms), daily tests, recovering patients, patients in the intensive care unit, daily intubated patients, and deaths forecasting and results are tested on Mean Absolute Percentage Error (MAPE) criterion. It is shown that this technique captured the system dynamic behavior in Turkey and made exact predictions with the use of real time dataset. tr_TR
dc.language.iso eng tr_TR
dc.relation.isversionof https://doi.org/10.1142/S2424922X21500066 tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject COVID-19 Data tr_TR
dc.subject Novel Forecasting Method tr_TR
dc.subject Moving Average tr_TR
dc.subject Classical Exponential Smoothing tr_TR
dc.subject Mean Absolute Percentage Error tr_TR
dc.title Exact Forecasting for COVID-19 Data: Case Study for Turkey tr_TR
dc.type article tr_TR
dc.relation.journal Advances in Data Science and Adaptive Analysis tr_TR
dc.contributor.authorID 26773 tr_TR
dc.identifier.volume 13 tr_TR
dc.identifier.issue 2 tr_TR
dc.contributor.department Çankaya Üniversitesi, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü tr_TR


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