- Gazi Mühendislik Bilimleri Dergisi
- Cilt: 9 Sayı: 4 - ICAIAME 2023 Özel Sayı
- Dynamic Mode Decomposition with Control: A Case Study Of Covid-19 and Vaccination
Dynamic Mode Decomposition with Control: A Case Study Of Covid-19 and Vaccination
Authors : Simge Kacar Eroğlu, Gamze Yüksel
Pages : 48-57
View : 29 | Download : 41
Publication Date : 2023-12-31
Article Type : Research
Abstract :Epidemic diseases have posed great threats to human societies throughout history and have seriously affected public health. Epidemic diseases can spread rapidly and cause major deaths and economic losses. Therefore, the control and management of epidemic diseases requires new approaches developed with scientific and technological developments. The method of Dynamic Mode Decomposition with Control (DMDc) is a machine learning technique that predicts the state of systems, that affect the dynamic system from the outside and change the nature of the system. This technique is used to examine how the variables, factors, and effects in the data are related to each other and how they change over time. In this article, the DMDc method used the weekly cumulative number of Covid-19 cases per 100 thousand of Turkey\'s 81 provinces between February 8 and September 11, 2021, as the situation matrix, and the total number of vaccines per 100 thousand in the same date range as the control matrix and then calculated error values of the DMD and DMDc are compared with under the different error metrics. In this paper,the number of cases and vaccines in the Turkish Ministry of Health TURCOVID-19 open data set was used.Keywords : dinamik mod ayrıştırması, kontrol, veriye dayalı dinamik sistemler, tekil değer ayrıştırması, makine öğrenmesi