Work

Probabilistic Forecasting Model for the COVID-19 Pandemic Based on the Composite Monte Carlo Model Integrated with Deep Learning and Fuzzy System

Year: 2022

Type: book-chapter

Source: Springer eBooks

DOI: 10.1007/978-3-030-95281-5_4

Authors: Simon James Fong, João Alexandre Lobo Marques, Gloria Li, Nilanjan Dey, Rubén González Crespo, Enrique Herrera-Viedma, Francisco Nauber Bernardo Gois, José Xavier Neto

Institutions: Chinese Academy of Sciences, University of Macau, Zhuhai Institute of Advanced Technology, University of Saint Joseph, Universidad Internacional de La Rioja, Universidad de Granada, Universidade de Fortaleza

Language: English

Topic: COVID-19 epidemiological studies

Subfield: Modeling and Simulation

Field: Mathematics

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W4293200225

FWCI: 1.757

Cites: 15

Cited by: 1

Related to: 10