Akademik Veri Yönetim Sistemi
III. International Conference on COVID-19, Ankara, Türkiye, 25 - 27 Aralık 2020, ss.1-8
The widespread outbreak of Coronavirus disease 2019 (COVID- 19) has
impacted almost all people in the world. Analysis and modelling of time
series of COVID-19 are needed to refine the measures and control the pandemic
and improve disease forecast. A lot of research has been done to forecast the global pandemic since the
world faced. Turkiye, which has with the highest percentage of foreign visitors
is one of the world's top ten destination countries, so the impact and future
behavior of COVID-19 in the country is really important. The main objective of
this paper is to extract forecasting models of the spread of coronavirus in Turkiye
in terms of confirmed cases. To the best of our knowledge, this is the first
attempt in the literature that aims to forecast the number of confirmed cases
using automatic programming method in Turkiye. Multi Gene GP is a high-level
automatic programming method that increases the efficiency of the standard GP
with a multi-tree modeling structure. The data of the previous 14 days were
used to forecast the 15th day with the models which are extracted by Multi Gene
Genetic Programming (Multi Gene GP). Since the pandemic reached in Turkiye on
11 March, all pandemic-related time series were trained dates between 11 March
– 19 December and we forecasted the next 14 days. Experimental results show
that, the proposed Multi Gene GP extracted successful forecsting models and had
the ability to forecast time series of COVID-19 in Turkiye.