Monthly runoff prediction by a multivariate hybrid model based on decomposition-normality and Lasso regression.

Kang, Yan; Cheng, Xiao; Chen, Peiru; Zhang, Shuo; Yang, Qinyu

Kang, Yan; Cheng, Xiao; Chen, Peiru; Zhang, Shuo; Yang, Qinyu.

Afiliação

Kang Y; College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling, Xianyang, 712100, China. kangyan@nwsuaf.edu.cn.
Cheng X; Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling, Xianyang, 712100, China. kangyan@nwsuaf.edu.cn.
Chen P; College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling, Xianyang, 712100, China.
Zhang S; College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling, Xianyang, 712100, China.
Yang Q; College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling, Xianyang, 712100, China.

Environ Sci Pollut Res Int ; 30(10): 27743-27762, 2023 Feb.

Article em En | MEDLINE | ID: mdl-36383318

Assuntos

Meteorologia; Humanos; Distribuição Normal

Palavras-chave

Decomposition-normality; Lasso regression; Monthly runoff prediction; Multivariate hybrid model

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Meteorologia Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google