On the implementation of a new version of the Weibull distribution and machine learning approach to model the COVID-19 data.

Zhou, Yinghui; Ahmad, Zubair; Almaspoor, Zahra; Khan, Faridoon; Tag-Eldin, Elsayed; Iqbal, Zahoor; El-Morshedy, Mahmoud

Zhou, Yinghui; Ahmad, Zubair; Almaspoor, Zahra; Khan, Faridoon; Tag-Eldin, Elsayed; Iqbal, Zahoor; El-Morshedy, Mahmoud.

Afiliación

Zhou Y; School of Information and Communication Engineering, Communication University of China, Beijing, China.
Ahmad Z; Department of Statistics, Yazd University, P. O. Box 89175-741, Yazd, Iran.
Almaspoor Z; Department of Statistics, Yazd University, P. O. Box 89175-741, Yazd, Iran.
Khan F; PIDE School of Economics, PIDE Islamabad 44000, Pakistan.
Tag-Eldin E; Faculty of Engineering and Technology, Future University in Egypt New Cairo 11835, Egypt.
Iqbal Z; Department of Mathematics, Quaid-i-Azam University, Islamabad 44000, Pakistan.
El-Morshedy M; Department of Mathematics, College of Science and Humanities in Al-Kharj, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia.

Math Biosci Eng ; 20(1): 337-364, 2023 01.

Article en En | MEDLINE | ID: mdl-36650769

Asunto(s)

COVID-19; Humanos; Reproducibilidad de los Resultados; COVID-19/epidemiología; Modelos Estadísticos; Redes Neurales de la Computación; Aprendizaje Automático

Palabras clave

family of distributions; healthcare sector; machine learning algorithms; mathematical properties; simulation; statistical modeling

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Math Biosci Eng Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google