Improvement of the global prediction system of the COVID-19 pandemic based on the ensemble empirical mode decomposition (EEMD) and autoregressive moving average (ARMA) model in a hybrid approach 基于集合经验模态分解和自回归-移动平均模型的 COVID-19 流行病全球预测系统预测结果改进

In 2020, the COVID-19 pandemic spreads rapidly around the world. To accurately predict the number of daily new cases in each country, Lanzhou University has established the Global Prediction System of the COVID-19 Pandemic (GPCP). In this article, the authors use the ensemble empirical mode decompos...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Chuwei, Huang, Jianping, Ji, Fei, Zhang, Li, Liu, Xiaoyue, Wei, Yun, Lian, Xinbo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7831456/
http://dx.doi.org/10.1016/j.aosl.2020.100019

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7831456/
http://dx.doi.org/10.1016/j.aosl.2020.100019

Ejemplares similares