NEURAL PREDICTOR DESIGN FOR COVID-19 CASES IN DIFFERENT REGIONS
Küçük Resim Yok
Tarih
2023
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Cefin Publishing House
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
COVID-19, which emerged in the past years, has affected human life in many different ways. The COVID-19 virus has spread very quickly around the world and has become a pandemic. In many applications, artificial neural networks are used to estimate system parameters in real-time or simulation-based methods. In this study, the daily and total number of cases in Turkey, Italy and India are predicted. Three alternative areas, with or without following rules, are chosen for the COVID-19 cases. For this prediction process, 3 different neural network methods are used: Nonlinear autoregressive neural network (NAR-NN), Adaptive-Network Based Fuzzy Inference Systems (ANFIS) and Autoregressive integrated moving average (ARIMA). The results obtained for 3 different neural networks are given with graphs and tables. The conclusion of this study may be used to improve the precaution for the pandemic. © 2023, Cefin Publishing House. All rights reserved.
Açıklama
Anahtar Kelimeler
ANFIS, ARIMA, Covid-19, NAR-NN, Prediction
Kaynak
International Journal of Mechatronics and Applied Mechanics
WoS Q Değeri
Scopus Q Değeri
Q4
Cilt
2023
Sayı
14
