A novel model for runoff prediction based on the ICEEMDAN-NGO-LSTM coupling.

Yang, Chen; Jiang, Yatao; Liu, Ying; Liu, Songlin; Liu, Fuping

Yang, Chen; Jiang, Yatao; Liu, Ying; Liu, Songlin; Liu, Fuping.

Afiliação

Yang C; Collaborative Innovation Center of Water Resources Efficient Utilization and Protection Engineering, Zhengzhou, 450046, China.
Jiang Y; School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.
Liu Y; College of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China. yingliu265@163.com.
Liu S; School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.
Liu F; School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.

Environ Sci Pollut Res Int ; 30(34): 82179-82188, 2023 Jul.

Article em En | MEDLINE | ID: mdl-37318729

Assuntos

Algoritmos; Hepatopatia Gordurosa não Alcoólica; Humanos; Hidrologia; Rios; Fatores de Tempo; Previsões

Palavras-chave

Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise; Long Short-Term Memory; Middle of Huai River; Northern Goshawk Optimization; Runoff prediction

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Hepatopatia Gordurosa não Alcoólica Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Environ Sci Pollut Res Int Assunto da revista: SAUDE AMBIENTAL / TOXICOLOGIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

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